---
OA_place: publisher
OA_type: hybrid
PlanS_conform: '1'
_id: '11442'
abstract:
- lang: eng
text: "Enabling additive manufacturing to employ a wide range of novel, functional
materials can be a major boost to this technology. However, making such materials
printable requires painstaking trial-and-error by an expert operator,\r\nas they
typically tend to exhibit peculiar rheological or hysteresis properties. Even
in the case of successfully finding the process parameters, there is no guarantee
of print-to-print consistency due to material differences between batches. These
challenges make closed-loop feedback an attractive option where the process parameters
are adjusted on-the-fly. There are several challenges for designing an efficient
controller: the deposition parameters are complex and highly coupled, artifacts
occur after long time horizons, simulating the deposition is computationally costly,
and learning on hardware is intractable. In this work, we demonstrate the feasibility
of learning a closed-loop control policy for additive manufacturing using reinforcement
learning. We show that approximate, but efficient, numerical simulation is\r\nsufficient
as long as it allows learning the behavioral patterns of deposition that translate
to real-world experiences. In combination with reinforcement learning, our model
can be used to discover control policies that outperform\r\nbaseline controllers.
Furthermore, the recovered policies have a minimal sim-to-real gap. We showcase
this by applying our control policy in-vivo on a single-layer, direct ink writing
printer. "
acknowledgement: "This work is graciously supported by the following grant agencies:
FWF Lise Meitner (Grant M 3319), SNSF (Grant 200502), ERC Starting Grant (MATERIALIZABLE-715767),
NSF (Grant IIS-181507).\r\n"
article_number: '112'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
orcid: 0000-0002-5062-4474
- first_name: Michael
full_name: Foshey, Michael
last_name: Foshey
- first_name: Jie
full_name: Xu, Jie
last_name: Xu
- first_name: Timothy
full_name: Erps, Timothy
last_name: Erps
- first_name: Vahid
full_name: Babaei, Vahid
last_name: Babaei
- first_name: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Szymon
full_name: Rusinkiewicz, Szymon
last_name: Rusinkiewicz
- first_name: Wojciech
full_name: Matusik, Wojciech
last_name: Matusik
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
citation:
ama: Piovarci M, Foshey M, Xu J, et al. Closed-loop control of direct ink writing
via reinforcement learning. ACM Transactions on Graphics. 2022;41(4). doi:10.1145/3528223.3530144
apa: Piovarci, M., Foshey, M., Xu, J., Erps, T., Babaei, V., Didyk, P., … Bickel,
B. (2022). Closed-loop control of direct ink writing via reinforcement learning.
ACM Transactions on Graphics. Association for Computing Machinery. https://doi.org/10.1145/3528223.3530144
chicago: Piovarci, Michael, Michael Foshey, Jie Xu, Timothy Erps, Vahid Babaei,
Piotr Didyk, Szymon Rusinkiewicz, Wojciech Matusik, and Bernd Bickel. “Closed-Loop
Control of Direct Ink Writing via Reinforcement Learning.” ACM Transactions
on Graphics. Association for Computing Machinery, 2022. https://doi.org/10.1145/3528223.3530144.
ieee: M. Piovarci et al., “Closed-loop control of direct ink writing via
reinforcement learning,” ACM Transactions on Graphics, vol. 41, no. 4.
Association for Computing Machinery, 2022.
ista: Piovarci M, Foshey M, Xu J, Erps T, Babaei V, Didyk P, Rusinkiewicz S, Matusik
W, Bickel B. 2022. Closed-loop control of direct ink writing via reinforcement
learning. ACM Transactions on Graphics. 41(4), 112.
mla: Piovarci, Michael, et al. “Closed-Loop Control of Direct Ink Writing via Reinforcement
Learning.” ACM Transactions on Graphics, vol. 41, no. 4, 112, Association
for Computing Machinery, 2022, doi:10.1145/3528223.3530144.
short: M. Piovarci, M. Foshey, J. Xu, T. Erps, V. Babaei, P. Didyk, S. Rusinkiewicz,
W. Matusik, B. Bickel, ACM Transactions on Graphics 41 (2022).
corr_author: '1'
date_created: 2022-06-10T06:41:47Z
date_published: 2022-06-01T00:00:00Z
date_updated: 2025-09-10T09:36:45Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3528223.3530144
ec_funded: 1
external_id:
arxiv:
- '2201.11819'
isi:
- '000830989200091'
file:
- access_level: open_access
checksum: 27f6fe41c6ff84d50445cc9b0176d45b
content_type: application/pdf
creator: dernst
date_created: 2022-06-28T08:32:58Z
date_updated: 2022-06-28T08:32:58Z
file_id: '11467'
file_name: 2022_ACM_acceptedversion_Piovarci.pdf
file_size: 33994829
relation: main_file
success: 1
file_date_updated: 2022-06-28T08:32:58Z
has_accepted_license: '1'
intvolume: ' 41'
isi: 1
issue: '4'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Submitted Version
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- 1557-7368
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
link:
- description: News on ISTA website
relation: press_release
url: https://ista.ac.at/en/news/machine-learning-3d-printing-fluids/
scopus_import: '1'
status: public
title: Closed-loop control of direct ink writing via reinforcement learning
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 41
year: '2022'
...
---
_id: '11735'
abstract:
- lang: eng
text: "Interlocking puzzles are intriguing geometric games where the puzzle pieces
are held together based on their geometric arrangement, preventing the puzzle
from falling apart. High-level-of-difficulty, or simply high-level, interlocking
puzzles are a subclass of interlocking puzzles that require multiple moves to
take out the first subassembly from the puzzle. Solving a high-level interlocking
puzzle is a challenging task since one has to explore many different configurations
of the puzzle pieces until reaching a configuration where the first subassembly
can be taken out. Designing a high-level interlocking puzzle with a user-specified
level of difficulty is even harder since the puzzle pieces have to be interlocking
in all the configurations before the first subassembly is taken out.\r\n\r\nIn
this paper, we present a computational approach to design high-level interlocking
puzzles. The core idea is to represent all possible configurations of an interlocking
puzzle as well as transitions among these configurations using a rooted, undirected
graph called a disassembly graph and leverage this graph to find a disassembly
plan that requires a minimal number of moves to take out the first subassembly
from the puzzle. At the design stage, our algorithm iteratively constructs the
geometry of each puzzle piece to expand the disassembly graph incrementally, aiming
to achieve a user-specified level of difficulty. We show that our approach allows
efficient generation of high-level interlocking puzzles of various shape complexities,
including new solutions not attainable by state-of-the-art approaches."
acknowledgement: "We thank the reviewers for the valuable comments, David Gontier
for sharing the source code of the baseline design approach, Christian Hafner for
proofreading the paper, Keenan Crane for the 3D model of Cow, and Thingiverse for
the 3D models of Moai and Owl. This work was supported by the SUTD Start-up Research
Grant (Number: SRG ISTD 2019 148), the Swiss National Science Foundation (NCCR Digital
Fabrication Agreement #51NF40-141853), and\r\nthe European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovation programme (Grant
Agreement No 715767 – MATERIALIZABLE)."
article_number: '150'
article_processing_charge: No
article_type: original
author:
- first_name: Rulin
full_name: Chen, Rulin
last_name: Chen
- first_name: Ziqi
full_name: Wang, Ziqi
last_name: Wang
- first_name: Peng
full_name: Song, Peng
last_name: Song
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
citation:
ama: Chen R, Wang Z, Song P, Bickel B. Computational design of high-level interlocking
puzzles. ACM Transactions on Graphics. 2022;41(4). doi:10.1145/3528223.3530071
apa: Chen, R., Wang, Z., Song, P., & Bickel, B. (2022). Computational design
of high-level interlocking puzzles. ACM Transactions on Graphics. Association
for Computing Machinery. https://doi.org/10.1145/3528223.3530071
chicago: Chen, Rulin, Ziqi Wang, Peng Song, and Bernd Bickel. “Computational Design
of High-Level Interlocking Puzzles.” ACM Transactions on Graphics. Association
for Computing Machinery, 2022. https://doi.org/10.1145/3528223.3530071.
ieee: R. Chen, Z. Wang, P. Song, and B. Bickel, “Computational design of high-level
interlocking puzzles,” ACM Transactions on Graphics, vol. 41, no. 4. Association
for Computing Machinery, 2022.
ista: Chen R, Wang Z, Song P, Bickel B. 2022. Computational design of high-level
interlocking puzzles. ACM Transactions on Graphics. 41(4), 150.
mla: Chen, Rulin, et al. “Computational Design of High-Level Interlocking Puzzles.”
ACM Transactions on Graphics, vol. 41, no. 4, 150, Association for Computing
Machinery, 2022, doi:10.1145/3528223.3530071.
short: R. Chen, Z. Wang, P. Song, B. Bickel, ACM Transactions on Graphics 41 (2022).
date_created: 2022-08-07T22:01:57Z
date_published: 2022-07-22T00:00:00Z
date_updated: 2025-04-14T07:28:57Z
day: '22'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3528223.3530071
ec_funded: 1
external_id:
isi:
- '000830989200018'
file:
- access_level: open_access
checksum: 0b51651be45b1b33f2072bd5d2686c69
content_type: application/pdf
creator: bbickel
date_created: 2022-08-28T07:56:19Z
date_updated: 2022-08-28T07:56:19Z
file_id: '11992'
file_name: Chen-2022-High-LevelPuzzle_authorVersion.pdf
file_size: 16896871
relation: main_file
success: 1
file_date_updated: 2022-08-28T07:56:19Z
has_accepted_license: '1'
intvolume: ' 41'
isi: 1
issue: '4'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Submitted Version
project:
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- 1557-7368
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
link:
- description: News on ISTA website
relation: press_release
url: https://ista.ac.at/en/news/unlocking-interlocking-riddles/
scopus_import: '1'
status: public
title: Computational design of high-level interlocking puzzles
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 41
year: '2022'
...
---
_id: '11993'
abstract:
- lang: eng
text: Moulding refers to a set of manufacturing techniques in which a mould, usually
a cavity or a solid frame, is used to shape a liquid or pliable material into
an object of the desired shape. The popularity of moulding comes from its effectiveness,
scalability and versatility in terms of employed materials. Its relevance as a
fabrication process is demonstrated by the extensive literature covering different
aspects related to mould design, from material flow simulation to the automation
of mould geometry design. In this state-of-the-art report, we provide an extensive
review of the automatic methods for the design of moulds, focusing on contributions
from a geometric perspective. We classify existing mould design methods based
on their computational approach and the nature of their target moulding process.
We summarize the relationships between computational approaches and moulding techniques,
highlighting their strengths and limitations. Finally, we discuss potential future
research directions.
article_processing_charge: No
article_type: original
author:
- first_name: Thomas
full_name: Alderighi, Thomas
last_name: Alderighi
- first_name: Luigi
full_name: Malomo, Luigi
last_name: Malomo
- first_name: Thomas
full_name: Auzinger, Thomas
id: 4718F954-F248-11E8-B48F-1D18A9856A87
last_name: Auzinger
orcid: 0000-0002-1546-3265
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Paulo
full_name: Cignoni, Paulo
last_name: Cignoni
- first_name: Nico
full_name: Pietroni, Nico
last_name: Pietroni
citation:
ama: Alderighi T, Malomo L, Auzinger T, Bickel B, Cignoni P, Pietroni N. State of
the art in computational mould design. Computer Graphics Forum. 2022;41(6):435-452.
doi:10.1111/cgf.14581
apa: Alderighi, T., Malomo, L., Auzinger, T., Bickel, B., Cignoni, P., & Pietroni,
N. (2022). State of the art in computational mould design. Computer Graphics
Forum. Wiley. https://doi.org/10.1111/cgf.14581
chicago: Alderighi, Thomas, Luigi Malomo, Thomas Auzinger, Bernd Bickel, Paulo Cignoni,
and Nico Pietroni. “State of the Art in Computational Mould Design.” Computer
Graphics Forum. Wiley, 2022. https://doi.org/10.1111/cgf.14581.
ieee: T. Alderighi, L. Malomo, T. Auzinger, B. Bickel, P. Cignoni, and N. Pietroni,
“State of the art in computational mould design,” Computer Graphics Forum,
vol. 41, no. 6. Wiley, pp. 435–452, 2022.
ista: Alderighi T, Malomo L, Auzinger T, Bickel B, Cignoni P, Pietroni N. 2022.
State of the art in computational mould design. Computer Graphics Forum. 41(6),
435–452.
mla: Alderighi, Thomas, et al. “State of the Art in Computational Mould Design.”
Computer Graphics Forum, vol. 41, no. 6, Wiley, 2022, pp. 435–52, doi:10.1111/cgf.14581.
short: T. Alderighi, L. Malomo, T. Auzinger, B. Bickel, P. Cignoni, N. Pietroni,
Computer Graphics Forum 41 (2022) 435–452.
corr_author: '1'
date_created: 2022-08-28T18:17:01Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2024-10-09T21:03:21Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1111/cgf.14581
external_id:
isi:
- '000842638900001'
file:
- access_level: open_access
checksum: c40cc8ceb7b7f0512172b883d712198e
content_type: application/pdf
creator: bbickel
date_created: 2022-08-28T18:18:08Z
date_updated: 2022-08-28T18:18:08Z
description: 'This is the pre-peer reviewed version of the following article: Alderighi,
T., Malomo, L., Auzinger, T., Bickel, B., Cignoni, P. and Pietroni, N. (2022),
State of the Art in Computational Mould Design. Computer Graphics Forum, which
has been published in final form at https://doi.org/10.1111/cgf.14581. This article
may be used for non-commercial purposes in accordance with Wiley Terms and Conditions
for Use of Self-Archived Versions.'
file_id: '11994'
file_name: star_molding_preprint.pdf
file_size: 32480850
relation: main_file
title: pre-peer reviewed version
file_date_updated: 2022-08-28T18:18:08Z
has_accepted_license: '1'
intvolume: ' 41'
isi: 1
issue: '6'
keyword:
- Computer Graphics and Computer-Aided Design
language:
- iso: eng
month: '09'
oa: 1
oa_version: Submitted Version
page: 435-452
publication: Computer Graphics Forum
publication_identifier:
eissn:
- 1467-8659
issn:
- 0167-7055
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: State of the art in computational mould design
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 41
year: '2022'
...
---
_id: '12135'
abstract:
- lang: eng
text: A good match of material appearance between real-world objects and their digital
on-screen representations is critical for many applications such as fabrication,
design, and e-commerce. However, faithful appearance reproduction is challenging,
especially for complex phenomena, such as gloss. In most cases, the view-dependent
nature of gloss and the range of luminance values required for reproducing glossy
materials exceeds the current capabilities of display devices. As a result, appearance
reproduction poses significant problems even with accurately rendered images.
This paper studies the gap between the gloss perceived from real-world objects
and their digital counterparts. Based on our psychophysical experiments on a wide
range of 3D printed samples and their corresponding photographs, we derive insights
on the influence of geometry, illumination, and the display’s brightness and measure
the change in gloss appearance due to the display limitations. Our evaluation
experiments demonstrate that using the prediction to correct material parameters
in a rendering system improves the match of gloss appearance between real objects
and their visualization on a display device.
acknowledgement: This work is supported by FWF Lise Meitner (Grant M 3319), European
Research Council (project CHAMELEON, Grant no. 682080), Swiss National Science Foundation
(Grant no. 200502), and academic gifts from Meta.
article_number: '35'
article_processing_charge: No
author:
- first_name: Bin
full_name: Chen, Bin
last_name: Chen
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
orcid: 0000-0002-5062-4474
- first_name: Chao
full_name: Wang, Chao
last_name: Wang
- first_name: Hans-Peter
full_name: Seidel, Hans-Peter
last_name: Seidel
- first_name: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Karol
full_name: Myszkowski, Karol
last_name: Myszkowski
- first_name: Ana
full_name: Serrano, Ana
last_name: Serrano
citation:
ama: 'Chen B, Piovarci M, Wang C, et al. Gloss management for consistent reproduction
of real and virtual objects. In: SIGGRAPH Asia 2022 Conference Papers.
Vol 2022. Association for Computing Machinery; 2022. doi:10.1145/3550469.3555406'
apa: 'Chen, B., Piovarci, M., Wang, C., Seidel, H.-P., Didyk, P., Myszkowski, K.,
& Serrano, A. (2022). Gloss management for consistent reproduction of real
and virtual objects. In SIGGRAPH Asia 2022 Conference Papers (Vol. 2022).
Daegu, South Korea: Association for Computing Machinery. https://doi.org/10.1145/3550469.3555406'
chicago: Chen, Bin, Michael Piovarci, Chao Wang, Hans-Peter Seidel, Piotr Didyk,
Karol Myszkowski, and Ana Serrano. “Gloss Management for Consistent Reproduction
of Real and Virtual Objects.” In SIGGRAPH Asia 2022 Conference Papers,
Vol. 2022. Association for Computing Machinery, 2022. https://doi.org/10.1145/3550469.3555406.
ieee: B. Chen et al., “Gloss management for consistent reproduction of real
and virtual objects,” in SIGGRAPH Asia 2022 Conference Papers, Daegu, South
Korea, 2022, vol. 2022.
ista: 'Chen B, Piovarci M, Wang C, Seidel H-P, Didyk P, Myszkowski K, Serrano A.
2022. Gloss management for consistent reproduction of real and virtual objects.
SIGGRAPH Asia 2022 Conference Papers. SIGGRAPH: Computer Graphics and Interactive
Techniques Conference vol. 2022, 35.'
mla: Chen, Bin, et al. “Gloss Management for Consistent Reproduction of Real and
Virtual Objects.” SIGGRAPH Asia 2022 Conference Papers, vol. 2022, 35,
Association for Computing Machinery, 2022, doi:10.1145/3550469.3555406.
short: B. Chen, M. Piovarci, C. Wang, H.-P. Seidel, P. Didyk, K. Myszkowski, A.
Serrano, in:, SIGGRAPH Asia 2022 Conference Papers, Association for Computing
Machinery, 2022.
conference:
end_date: 2022-12-09
location: Daegu, South Korea
name: 'SIGGRAPH: Computer Graphics and Interactive Techniques Conference'
start_date: 2022-12-06
date_created: 2023-01-12T12:03:56Z
date_published: 2022-11-01T00:00:00Z
date_updated: 2025-09-10T09:47:32Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3550469.3555406
external_id:
isi:
- '001074614400031'
file:
- access_level: open_access
checksum: f47f3215ab8bb919e3546b3438c34c21
content_type: application/pdf
creator: dernst
date_created: 2023-01-24T07:35:21Z
date_updated: 2023-01-24T07:35:21Z
file_id: '12351'
file_name: 2022_ACM_SIGGRAPH_Chen.pdf
file_size: 28826826
relation: main_file
success: 1
file_date_updated: 2023-01-24T07:35:21Z
has_accepted_license: '1'
intvolume: ' 2022'
isi: 1
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
publication: SIGGRAPH Asia 2022 Conference Papers
publication_identifier:
isbn:
- '9781450394703'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Gloss management for consistent reproduction of real and virtual objects
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 2022
year: '2022'
...
---
_id: '12452'
abstract:
- lang: eng
text: Portrait viewpoint and illumination editing is an important problem with several
applications in VR/AR, movies, and photography. Comprehensive knowledge of geometry
and illumination is critical for obtaining photorealistic results. Current methods
are unable to explicitly model in 3D while handing both viewpoint and illumination
editing from a single image. In this paper, we propose VoRF, a novel approach
that can take even a single portrait image as input and relight human heads under
novel illuminations that can be viewed from arbitrary viewpoints. VoRF represents
a human head as a continuous volumetric field and learns a prior model of human
heads using a coordinate-based MLP with separate latent spaces for identity and
illumination. The prior model is learnt in an auto-decoder manner over a diverse
class of head shapes and appearances, allowing VoRF to generalize to novel test
identities from a single input image. Additionally, VoRF has a reflectance MLP
that uses the intermediate features of the prior model for rendering One-Light-at-A-Time
(OLAT) images under novel views. We synthesize novel illuminations by combining
these OLAT images with target environment maps. Qualitative and quantitative evaluations
demonstrate the effectiveness of VoRF for relighting and novel view synthesis
even when applied to unseen subjects under uncontrolled illuminations.
acknowledgement: This work was supported by the ERC Consolidator Grant 4DReply (770784).
article_number: '708'
article_processing_charge: No
author:
- first_name: Pramod
full_name: Rao, Pramod
last_name: Rao
- first_name: Mallikarjun
full_name: B R, Mallikarjun
last_name: B R
- first_name: Gereon
full_name: Fox, Gereon
last_name: Fox
- first_name: Tim
full_name: Weyrich, Tim
last_name: Weyrich
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Hans-Peter
full_name: Seidel, Hans-Peter
last_name: Seidel
- first_name: Hanspeter
full_name: Pfister, Hanspeter
last_name: Pfister
- first_name: Wojciech
full_name: Matusik, Wojciech
last_name: Matusik
- first_name: Ayush
full_name: Tewari, Ayush
last_name: Tewari
- first_name: Christian
full_name: Theobalt, Christian
last_name: Theobalt
- first_name: Mohamed
full_name: Elgharib, Mohamed
last_name: Elgharib
citation:
ama: 'Rao P, B R M, Fox G, et al. VoRF: Volumetric Relightable Faces. In: 33rd
British Machine Vision Conference. British Machine Vision Association and
Society for Pattern Recognition; 2022.'
apa: 'Rao, P., B R, M., Fox, G., Weyrich, T., Bickel, B., Seidel, H.-P., … Elgharib,
M. (2022). VoRF: Volumetric Relightable Faces. In 33rd British Machine Vision
Conference. London, United Kingdom: British Machine Vision Association and
Society for Pattern Recognition.'
chicago: 'Rao, Pramod, Mallikarjun B R, Gereon Fox, Tim Weyrich, Bernd Bickel, Hans-Peter
Seidel, Hanspeter Pfister, et al. “VoRF: Volumetric Relightable Faces.” In 33rd
British Machine Vision Conference. British Machine Vision Association and
Society for Pattern Recognition, 2022.'
ieee: 'P. Rao et al., “VoRF: Volumetric Relightable Faces,” in 33rd British
Machine Vision Conference, London, United Kingdom, 2022.'
ista: 'Rao P, B R M, Fox G, Weyrich T, Bickel B, Seidel H-P, Pfister H, Matusik
W, Tewari A, Theobalt C, Elgharib M. 2022. VoRF: Volumetric Relightable Faces.
33rd British Machine Vision Conference. BMVC: British Machine Vision Conference,
708.'
mla: 'Rao, Pramod, et al. “VoRF: Volumetric Relightable Faces.” 33rd British
Machine Vision Conference, 708, British Machine Vision Association and Society
for Pattern Recognition, 2022.'
short: P. Rao, M. B R, G. Fox, T. Weyrich, B. Bickel, H.-P. Seidel, H. Pfister,
W. Matusik, A. Tewari, C. Theobalt, M. Elgharib, in:, 33rd British Machine Vision
Conference, British Machine Vision Association and Society for Pattern Recognition,
2022.
conference:
end_date: 2022-11-24
location: London, United Kingdom
name: 'BMVC: British Machine Vision Conference'
start_date: 2022-11-21
date_created: 2023-01-30T10:47:06Z
date_published: 2022-12-01T00:00:00Z
date_updated: 2023-10-31T08:40:55Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
file:
- access_level: open_access
checksum: b60b70bb48700aee709c85a69231821d
content_type: application/pdf
creator: bbickel
date_created: 2023-01-30T10:48:18Z
date_updated: 2023-01-30T10:48:18Z
file_id: '12453'
file_name: vorf_main.pdf
file_size: 5202710
relation: main_file
title: 'VoRF: Volumetric Relightable Faces'
- access_level: open_access
checksum: ce5f4ce66eaaa1590ee5df989fca6f61
content_type: application/pdf
creator: bbickel
date_created: 2023-01-30T10:48:29Z
date_updated: 2023-01-30T10:48:29Z
file_id: '12454'
file_name: vorf_supp.pdf
file_size: 37953188
relation: supplementary_material
title: 'VoRF: Volumetric Relightable Faces – SUPPLEMENTAL MATERIAL –'
- access_level: open_access
checksum: 08aecca434b08fee75ee1efe87943718
content_type: video/mp4
creator: bbickel
date_created: 2023-01-30T10:48:37Z
date_updated: 2023-01-30T10:48:37Z
file_id: '12455'
file_name: video.mp4
file_size: 57855492
relation: supplementary_material
file_date_updated: 2023-01-30T10:48:37Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://bmvc2022.mpi-inf.mpg.de/708/
month: '12'
oa: 1
oa_version: Published Version
publication: 33rd British Machine Vision Conference
publication_status: published
publisher: British Machine Vision Association and Society for Pattern Recognition
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'VoRF: Volumetric Relightable Faces'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '17065'
abstract:
- lang: eng
text: Past work on optimizing fabrication plans given a carpentry design can provide
Pareto-optimal plans trading off between material waste, fabrication time, precision,
and other considerations. However, when developing fabrication plans, experts
rarely restrict to a single design, instead considering families of design variations,
sometimes adjusting designs to simplify fabrication. Jointly exploring the design
and fabrication plan spaces for each design is intractable using current techniques.
We present a new approach to jointly optimize design and fabrication plans for
carpentered objects. To make this bi-level optimization tractable, we adapt recent
work from program synthesis based on equality graphs (e-graphs), which encode
sets of equivalent programs. Our insight is that subproblems within our bi-level
problem share significant substructures. By representing both designs and fabrication
plans in a new bag of parts (BOP) e-graph, we amortize the cost of optimizing
design components shared among multiple candidates. Even using BOP e-graphs, the
optimization space grows quickly in practice. Hence, we also show how a feedback-guided
search strategy dubbed Iterative Contraction and Expansion on E-graphs (ICEE)
can keep the size of the e-graph manageable and direct the search towards promising
candidates. We illustrate the advantages of our pipeline through examples from
the carpentry domain.
acknowledgement: The authors would like to thank anonymous reviewers for their helpful
feedback; Haomiao Wu for her contribution to the algorithm development in the early
stage of the project; Elias Baldwin, David Tsay, Alexander Lefort, and Qiyang Tan
for helping the experiments.
article_number: '32'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Haisen
full_name: Zhao, Haisen
id: fb7f793a-80d1-11eb-8869-d56e5b2a8ff4
last_name: Zhao
orcid: 0000-0002-6389-1045
- first_name: Max
full_name: Willsey, Max
last_name: Willsey
- first_name: Amy
full_name: Zhu, Amy
last_name: Zhu
- first_name: Chandrakana
full_name: Nandi, Chandrakana
last_name: Nandi
- first_name: Zachary
full_name: Tatlock, Zachary
last_name: Tatlock
- first_name: Justin
full_name: Solomon, Justin
last_name: Solomon
- first_name: Adriana
full_name: Schulz, Adriana
last_name: Schulz
citation:
ama: Zhao H, Willsey M, Zhu A, et al. Co-optimization of design and fabrication
plans for carpentry. ACM Transactions on Graphics. 2022;41(3). doi:10.1145/3508499
apa: Zhao, H., Willsey, M., Zhu, A., Nandi, C., Tatlock, Z., Solomon, J., &
Schulz, A. (2022). Co-optimization of design and fabrication plans for carpentry.
ACM Transactions on Graphics. Association for Computing Machinery. https://doi.org/10.1145/3508499
chicago: Zhao, Haisen, Max Willsey, Amy Zhu, Chandrakana Nandi, Zachary Tatlock,
Justin Solomon, and Adriana Schulz. “Co-Optimization of Design and Fabrication
Plans for Carpentry.” ACM Transactions on Graphics. Association for Computing
Machinery, 2022. https://doi.org/10.1145/3508499.
ieee: H. Zhao et al., “Co-optimization of design and fabrication plans for
carpentry,” ACM Transactions on Graphics, vol. 41, no. 3. Association for
Computing Machinery, 2022.
ista: Zhao H, Willsey M, Zhu A, Nandi C, Tatlock Z, Solomon J, Schulz A. 2022. Co-optimization
of design and fabrication plans for carpentry. ACM Transactions on Graphics. 41(3),
32.
mla: Zhao, Haisen, et al. “Co-Optimization of Design and Fabrication Plans for Carpentry.”
ACM Transactions on Graphics, vol. 41, no. 3, 32, Association for Computing
Machinery, 2022, doi:10.1145/3508499.
short: H. Zhao, M. Willsey, A. Zhu, C. Nandi, Z. Tatlock, J. Solomon, A. Schulz,
ACM Transactions on Graphics 41 (2022).
date_created: 2024-05-29T06:09:23Z
date_published: 2022-03-09T00:00:00Z
date_updated: 2024-08-06T07:03:14Z
day: '09'
department:
- _id: BeBi
doi: 10.1145/3508499
external_id:
arxiv:
- '2107.12265'
intvolume: ' 41'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2107.12265
month: '03'
oa: 1
oa_version: Preprint
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- 1557-7368
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Co-optimization of design and fabrication plans for carpentry
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 41
year: '2022'
...
---
OA_place: repository
_id: '11943'
abstract:
- lang: eng
text: Complex wiring between neurons underlies the information-processing network
enabling all brain functions, including cognition and memory. For understanding
how the network is structured, processes information, and changes over time, comprehensive
visualization of the architecture of living brain tissue with its cellular and
molecular components would open up major opportunities. However, electron microscopy
(EM) provides nanometre-scale resolution required for full in-silico
reconstruction1–5, yet is limited to fixed specimens and
static representations. Light microscopy allows live observation, with super-resolution
approaches6–12 facilitating nanoscale visualization, but
comprehensive 3D-reconstruction of living brain tissue has been hindered by tissue
photo-burden, photobleaching, insufficient 3D-resolution, and inadequate signal-to-noise
ratio (SNR). Here we demonstrate saturated reconstruction of living brain tissue.
We developed an integrated imaging and analysis technology, adapting stimulated
emission depletion (STED) microscopy6,13 in extracellularly
labelled tissue14 for high SNR and near-isotropic resolution.
Centrally, a two-stage deep-learning approach leveraged previously obtained information
on sample structure to drastically reduce photo-burden and enable automated volumetric
reconstruction down to single synapse level. Live reconstruction provides unbiased
analysis of tissue architecture across time in relation to functional activity
and targeted activation, and contextual understanding of molecular labelling.
This adoptable technology will facilitate novel insights into the dynamic functional
architecture of living brain tissue.
article_processing_charge: No
author:
- first_name: Philipp
full_name: Velicky, Philipp
id: 39BDC62C-F248-11E8-B48F-1D18A9856A87
last_name: Velicky
orcid: 0000-0002-2340-7431
- first_name: Eder
full_name: Miguel Villalba, Eder
id: 3FB91342-F248-11E8-B48F-1D18A9856A87
last_name: Miguel Villalba
orcid: 0000-0001-5665-0430
- first_name: Julia M
full_name: Michalska, Julia M
id: 443DB6DE-F248-11E8-B48F-1D18A9856A87
last_name: Michalska
orcid: 0000-0003-3862-1235
- first_name: Donglai
full_name: Wei, Donglai
last_name: Wei
- first_name: Zudi
full_name: Lin, Zudi
last_name: Lin
- first_name: Jake
full_name: Watson, Jake
id: 63836096-4690-11EA-BD4E-32803DDC885E
last_name: Watson
orcid: 0000-0002-8698-3823
- first_name: Jakob
full_name: Troidl, Jakob
last_name: Troidl
- first_name: Johanna
full_name: Beyer, Johanna
last_name: Beyer
- first_name: Yoav
full_name: Ben Simon, Yoav
id: 43DF3136-F248-11E8-B48F-1D18A9856A87
last_name: Ben Simon
- first_name: Christoph M
full_name: Sommer, Christoph M
id: 4DF26D8C-F248-11E8-B48F-1D18A9856A87
last_name: Sommer
orcid: 0000-0003-1216-9105
- first_name: Wiebke
full_name: Jahr, Wiebke
id: 425C1CE8-F248-11E8-B48F-1D18A9856A87
last_name: Jahr
orcid: 0000-0003-0201-2315
- first_name: Alban
full_name: Cenameri, Alban
id: 9ac8f577-2357-11eb-997a-e566c5550886
last_name: Cenameri
- first_name: Johannes
full_name: Broichhagen, Johannes
last_name: Broichhagen
- first_name: Seth G. N.
full_name: Grant, Seth G. N.
last_name: Grant
- first_name: Peter M
full_name: Jonas, Peter M
id: 353C1B58-F248-11E8-B48F-1D18A9856A87
last_name: Jonas
orcid: 0000-0001-5001-4804
- first_name: Gaia
full_name: Novarino, Gaia
id: 3E57A680-F248-11E8-B48F-1D18A9856A87
last_name: Novarino
orcid: 0000-0002-7673-7178
- first_name: Hanspeter
full_name: Pfister, Hanspeter
last_name: Pfister
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Johann G
full_name: Danzl, Johann G
id: 42EFD3B6-F248-11E8-B48F-1D18A9856A87
last_name: Danzl
orcid: 0000-0001-8559-3973
citation:
ama: Velicky P, Miguel Villalba E, Michalska JM, et al. Saturated reconstruction
of living brain tissue. bioRxiv. doi:10.1101/2022.03.16.484431
apa: Velicky, P., Miguel Villalba, E., Michalska, J. M., Wei, D., Lin, Z., Watson,
J., … Danzl, J. G. (n.d.). Saturated reconstruction of living brain tissue. bioRxiv.
Cold Spring Harbor Laboratory. https://doi.org/10.1101/2022.03.16.484431
chicago: Velicky, Philipp, Eder Miguel Villalba, Julia M Michalska, Donglai Wei,
Zudi Lin, Jake Watson, Jakob Troidl, et al. “Saturated Reconstruction of Living
Brain Tissue.” BioRxiv. Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/2022.03.16.484431.
ieee: P. Velicky et al., “Saturated reconstruction of living brain tissue,”
bioRxiv. Cold Spring Harbor Laboratory.
ista: Velicky P, Miguel Villalba E, Michalska JM, Wei D, Lin Z, Watson J, Troidl
J, Beyer J, Ben Simon Y, Sommer CM, Jahr W, Cenameri A, Broichhagen J, Grant SGN,
Jonas PM, Novarino G, Pfister H, Bickel B, Danzl JG. Saturated reconstruction
of living brain tissue. bioRxiv, 10.1101/2022.03.16.484431.
mla: Velicky, Philipp, et al. “Saturated Reconstruction of Living Brain Tissue.”
BioRxiv, Cold Spring Harbor Laboratory, doi:10.1101/2022.03.16.484431.
short: P. Velicky, E. Miguel Villalba, J.M. Michalska, D. Wei, Z. Lin, J. Watson,
J. Troidl, J. Beyer, Y. Ben Simon, C.M. Sommer, W. Jahr, A. Cenameri, J. Broichhagen,
S.G.N. Grant, P.M. Jonas, G. Novarino, H. Pfister, B. Bickel, J.G. Danzl, BioRxiv
(n.d.).
corr_author: '1'
date_created: 2022-08-23T11:07:59Z
date_published: 2022-05-09T00:00:00Z
date_updated: 2026-07-03T22:30:45Z
day: '09'
department:
- _id: PeJo
- _id: GaNo
- _id: BeBi
- _id: JoDa
doi: 10.1101/2022.03.16.484431
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/2022.03.16.484431
month: '05'
oa: 1
oa_version: Preprint
publication: bioRxiv
publication_status: draft
publisher: Cold Spring Harbor Laboratory
related_material:
record:
- id: '13267'
relation: later_version
status: public
- id: '12470'
relation: dissertation_contains
status: public
status: public
title: Saturated reconstruction of living brain tissue
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '10148'
abstract:
- lang: eng
text: Tactile feedback of an object’s surface enables us to discern its material
properties and affordances. This understanding is used in digital fabrication
processes by creating objects with high-resolution surface variations to influence
a user’s tactile perception. As the design of such surface haptics commonly relies
on knowledge from real-life experiences, it is unclear how to adapt this information
for digital design methods. In this work, we investigate replicating the haptics
of real materials. Using an existing process for capturing an object’s microgeometry,
we digitize and reproduce the stable surface information of a set of 15 fabric
samples. In a psychophysical experiment, we evaluate the tactile qualities of
our set of original samples and their replicas. From our results, we see that
direct reproduction of surface variations is able to influence different psychophysical
dimensions of the tactile perception of surface textures. While the fabrication
process did not preserve all properties, our approach underlines that replication
of surface microgeometries benefits fabrication methods in terms of haptic perception
by covering a large range of tactile variations. Moreover, by changing the surface
structure of a single fabricated material, its material perception can be influenced.
We conclude by proposing strategies for capturing and reproducing digitized textures
to better resemble the perceived haptics of the originals.
acknowledgement: Our gratitude goes out to Kamila Mushkina, Akhmajon Makhsadov, Jordan
Espenshade, Bruno Fruchard, Roland Bennewitz, and Robert Drumm. This project has
received funding from the EU’s Horizon 2020 research and innovation programme, under
the Marie Skłodowska-Curie grant agreement No 642841 (DISTRO).
article_processing_charge: No
author:
- first_name: Donald
full_name: Degraen, Donald
last_name: Degraen
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
orcid: 0000-0002-5062-4474
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Antonio
full_name: Kruger, Antonio
last_name: Kruger
citation:
ama: 'Degraen D, Piovarci M, Bickel B, Kruger A. Capturing tactile properties of
real surfaces for haptic reproduction. In: 34th Annual ACM Symposium. Association
for Computing Machinery; 2021:954-971. doi:10.1145/3472749.3474798'
apa: 'Degraen, D., Piovarci, M., Bickel, B., & Kruger, A. (2021). Capturing
tactile properties of real surfaces for haptic reproduction. In 34th Annual
ACM Symposium (pp. 954–971). Virtual: Association for Computing Machinery.
https://doi.org/10.1145/3472749.3474798'
chicago: Degraen, Donald, Michael Piovarci, Bernd Bickel, and Antonio Kruger. “Capturing
Tactile Properties of Real Surfaces for Haptic Reproduction.” In 34th Annual
ACM Symposium, 954–71. Association for Computing Machinery, 2021. https://doi.org/10.1145/3472749.3474798.
ieee: D. Degraen, M. Piovarci, B. Bickel, and A. Kruger, “Capturing tactile properties
of real surfaces for haptic reproduction,” in 34th Annual ACM Symposium,
Virtual, 2021, pp. 954–971.
ista: 'Degraen D, Piovarci M, Bickel B, Kruger A. 2021. Capturing tactile properties
of real surfaces for haptic reproduction. 34th Annual ACM Symposium. UIST: User
Interface Software and Technology, 954–971.'
mla: Degraen, Donald, et al. “Capturing Tactile Properties of Real Surfaces for
Haptic Reproduction.” 34th Annual ACM Symposium, Association for Computing
Machinery, 2021, pp. 954–71, doi:10.1145/3472749.3474798.
short: D. Degraen, M. Piovarci, B. Bickel, A. Kruger, in:, 34th Annual ACM Symposium,
Association for Computing Machinery, 2021, pp. 954–971.
conference:
end_date: 2021-10-14
location: Virtual
name: 'UIST: User Interface Software and Technology'
start_date: 2021-10-10
date_created: 2021-10-18T07:36:11Z
date_published: 2021-10-10T00:00:00Z
date_updated: 2025-03-31T15:58:15Z
day: '10'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3472749.3474798
ec_funded: 1
file:
- access_level: open_access
checksum: b0b26464df79b3a59e8ed82e4e19ab15
content_type: application/pdf
creator: bbickel
date_created: 2021-10-18T07:36:03Z
date_updated: 2021-10-18T07:36:03Z
file_id: '10149'
file_name: degraen-UIST2021_Texture_Appropriation_CR_preprint.pdf
file_size: 29796364
relation: main_file
file_date_updated: 2021-10-18T07:36:03Z
has_accepted_license: '1'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Preprint
page: 954-971
project:
- _id: 2508E324-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '642841'
name: Distributed 3D Object Design
publication: 34th Annual ACM Symposium
publication_identifier:
isbn:
- 978-1-4503-8635-7
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Capturing tactile properties of real surfaces for haptic reproduction
type: conference
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '10184'
abstract:
- lang: eng
text: "We introduce a novel technique to automatically decompose an input object’s
volume into a set of parts that can be represented by two opposite height fields.
Such decomposition enables the manufacturing of individual parts using two-piece
reusable rigid molds. Our decomposition strategy relies on a new energy formulation
that utilizes a pre-computed signal on the mesh volume representing the accessibility
for a predefined set of extraction directions. Thanks to this novel formulation,
our method allows for efficient optimization of a fabrication-aware partitioning
of volumes in a completely\r\nautomatic way. We demonstrate the efficacy of our
approach by generating valid volume partitionings for a wide range of complex
objects and physically reproducing several of them."
acknowledgement: 'The authors thank Marco Callieri for all his precious help with
the resin casts. The models used in the paper are courtesy of the Stanford 3D Scanning
Repository, the AIM@SHAPE Shape Repository, and Thingi10K Repository. The research
was partially funded by the European Research Council (ERC) MATERIALIZABLE: Intelligent
fabrication-oriented computational design and modeling (grant no. 715767).'
article_number: '272'
article_processing_charge: No
article_type: original
author:
- first_name: Thomas
full_name: Alderighi, Thomas
last_name: Alderighi
- first_name: Luigi
full_name: Malomo, Luigi
last_name: Malomo
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Paolo
full_name: Cignoni, Paolo
last_name: Cignoni
- first_name: Nico
full_name: Pietroni, Nico
last_name: Pietroni
citation:
ama: Alderighi T, Malomo L, Bickel B, Cignoni P, Pietroni N. Volume decomposition
for two-piece rigid casting. ACM Transactions on Graphics. 2021;40(6).
doi:10.1145/3478513.3480555
apa: Alderighi, T., Malomo, L., Bickel, B., Cignoni, P., & Pietroni, N. (2021).
Volume decomposition for two-piece rigid casting. ACM Transactions on Graphics.
Association for Computing Machinery. https://doi.org/10.1145/3478513.3480555
chicago: Alderighi, Thomas, Luigi Malomo, Bernd Bickel, Paolo Cignoni, and Nico
Pietroni. “Volume Decomposition for Two-Piece Rigid Casting.” ACM Transactions
on Graphics. Association for Computing Machinery, 2021. https://doi.org/10.1145/3478513.3480555.
ieee: T. Alderighi, L. Malomo, B. Bickel, P. Cignoni, and N. Pietroni, “Volume decomposition
for two-piece rigid casting,” ACM Transactions on Graphics, vol. 40, no.
6. Association for Computing Machinery, 2021.
ista: Alderighi T, Malomo L, Bickel B, Cignoni P, Pietroni N. 2021. Volume decomposition
for two-piece rigid casting. ACM Transactions on Graphics. 40(6), 272.
mla: Alderighi, Thomas, et al. “Volume Decomposition for Two-Piece Rigid Casting.”
ACM Transactions on Graphics, vol. 40, no. 6, 272, Association for Computing
Machinery, 2021, doi:10.1145/3478513.3480555.
short: T. Alderighi, L. Malomo, B. Bickel, P. Cignoni, N. Pietroni, ACM Transactions
on Graphics 40 (2021).
date_created: 2021-10-27T07:08:19Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2025-04-14T07:28:57Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3478513.3480555
ec_funded: 1
external_id:
isi:
- '000729846700077'
file:
- access_level: open_access
checksum: 384ece7a9ad1026787ba9560b04336d5
content_type: application/pdf
creator: bbickel
date_created: 2021-10-27T07:08:07Z
date_updated: 2021-10-27T07:08:07Z
file_id: '10185'
file_name: rigidmolds-authorversion.pdf
file_size: 107708317
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intvolume: ' 40'
isi: 1
issue: '6'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://vcg.isti.cnr.it/Publications/2021/AMBCP21
month: '12'
oa: 1
oa_version: Submitted Version
project:
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- '1557-7368 '
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Volume decomposition for two-piece rigid casting
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 40
year: '2021'
...
---
_id: '10574'
abstract:
- lang: eng
text: 'The understanding of material appearance perception is a complex problem
due to interactions between material reflectance, surface geometry, and illumination.
Recently, Serrano et al. collected the largest dataset to date with subjective
ratings of material appearance attributes, including glossiness, metallicness,
sharpness and contrast of reflections. In this work, we make use of their dataset
to investigate for the first time the impact of the interactions between illumination,
geometry, and eight different material categories in perceived appearance attributes.
After an initial analysis, we select for further analysis the four material categories
that cover the largest range for all perceptual attributes: fabric, plastic, ceramic,
and metal. Using a cumulative link mixed model (CLMM) for robust regression, we
discover interactions between these material categories and four representative
illuminations and object geometries. We believe that our findings contribute to
expanding the knowledge on material appearance perception and can be useful for
many applications, such as scene design, where any particular material in a given
shape can be aligned with dominant classes of illumination, so that a desired
strength of appearance attributes can be achieved.'
acknowledgement: This project has received funding from the European Union’s Horizon
2020 research and innovation programme under the Marie Sklodowska-Curie, grant agreement
N∘ 765911 (RealVision) and from the European Research Council (ERC), grant agreement
N∘ 804226 (PERDY). Open Access funding enabled and organized by Projekt DEAL.
article_processing_charge: Yes
article_type: original
author:
- first_name: Bin
full_name: Chen, Bin
last_name: Chen
- first_name: Chao
full_name: Wang, Chao
last_name: Wang
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
orcid: 0000-0002-5062-4474
- first_name: Hans Peter
full_name: Seidel, Hans Peter
last_name: Seidel
- first_name: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Karol
full_name: Myszkowski, Karol
last_name: Myszkowski
- first_name: Ana
full_name: Serrano, Ana
last_name: Serrano
citation:
ama: Chen B, Wang C, Piovarci M, et al. The effect of geometry and illumination
on appearance perception of different material categories. Visual Computer.
2021;37(12):2975-2987. doi:10.1007/s00371-021-02227-x
apa: Chen, B., Wang, C., Piovarci, M., Seidel, H. P., Didyk, P., Myszkowski, K.,
& Serrano, A. (2021). The effect of geometry and illumination on appearance
perception of different material categories. Visual Computer. Springer
Nature. https://doi.org/10.1007/s00371-021-02227-x
chicago: Chen, Bin, Chao Wang, Michael Piovarci, Hans Peter Seidel, Piotr Didyk,
Karol Myszkowski, and Ana Serrano. “The Effect of Geometry and Illumination on
Appearance Perception of Different Material Categories.” Visual Computer.
Springer Nature, 2021. https://doi.org/10.1007/s00371-021-02227-x.
ieee: B. Chen et al., “The effect of geometry and illumination on appearance
perception of different material categories,” Visual Computer, vol. 37,
no. 12. Springer Nature, pp. 2975–2987, 2021.
ista: Chen B, Wang C, Piovarci M, Seidel HP, Didyk P, Myszkowski K, Serrano A. 2021.
The effect of geometry and illumination on appearance perception of different
material categories. Visual Computer. 37(12), 2975–2987.
mla: Chen, Bin, et al. “The Effect of Geometry and Illumination on Appearance Perception
of Different Material Categories.” Visual Computer, vol. 37, no. 12, Springer
Nature, 2021, pp. 2975–87, doi:10.1007/s00371-021-02227-x.
short: B. Chen, C. Wang, M. Piovarci, H.P. Seidel, P. Didyk, K. Myszkowski, A. Serrano,
Visual Computer 37 (2021) 2975–2987.
date_created: 2021-12-26T23:01:26Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2023-08-17T06:29:34Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1007/s00371-021-02227-x
external_id:
isi:
- '000673536600003'
file:
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content_type: application/pdf
creator: cchlebak
date_created: 2021-12-27T13:51:08Z
date_updated: 2021-12-27T13:51:08Z
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language:
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month: '12'
oa: 1
oa_version: Published Version
page: 2975-2987
publication: Visual Computer
publication_identifier:
eissn:
- 1432-2315
issn:
- 0178-2789
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
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title: The effect of geometry and illumination on appearance perception of different
material categories
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image: /images/cc_by.png
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short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 37
year: '2021'
...
---
_id: '9241'
abstract:
- lang: eng
text: 'Volumetric light transport is a pervasive physical phenomenon, and therefore
its accurate simulation is important for a broad array of disciplines. While suitable
mathematical models for computing the transport are now available, obtaining the
necessary material parameters needed to drive such simulations is a challenging
task: direct measurements of these parameters from material samples are seldom
possible. Building on the inverse scattering paradigm, we present a novel measurement
approach which indirectly infers the transport parameters from extrinsic observations
of multiple-scattered radiance. The novelty of the proposed approach lies in replacing
structured illumination with a structured reflector bonded to the sample, and
a robust fitting procedure that largely compensates for potential systematic errors
in the calibration of the setup. We show the feasibility of our approach by validating
simulations of complex 3D compositions of the measured materials against physical
prints, using photo-polymer resins. As presented in this paper, our technique
yields colorspace data suitable for accurate appearance reproduction in the area
of 3D printing. Beyond that, and without fundamental changes to the basic measurement
methodology, it could equally well be used to obtain spectral measurements that
are useful for other application areas.'
acknowledgement: "H2020 Marie Skłodowska-Curie Actions (642841); European Research
Council (715767); Grantová Agentura České Republiky (16-08111S, 16-18964S); Univerzita
Karlova v Praze (SVV-2017-260452); Engineering and Physical Sciences Research Council
(EP/K023578/1).\r\nWe are grateful to Stratasys Ltd. for access to the voxel-level
print interface of the J750\r\nmachine."
article_processing_charge: No
article_type: original
author:
- first_name: Oskar
full_name: Elek, Oskar
last_name: Elek
- first_name: Ran
full_name: Zhang, Ran
id: 4DDBCEB0-F248-11E8-B48F-1D18A9856A87
last_name: Zhang
orcid: 0000-0002-3808-281X
- first_name: Denis
full_name: Sumin, Denis
last_name: Sumin
- first_name: Karol
full_name: Myszkowski, Karol
last_name: Myszkowski
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Alexander
full_name: Wilkie, Alexander
last_name: Wilkie
- first_name: Jaroslav
full_name: Křivánek, Jaroslav
last_name: Křivánek
- first_name: Tim
full_name: Weyrich, Tim
last_name: Weyrich
citation:
ama: Elek O, Zhang R, Sumin D, et al. Robust and practical measurement of volume
transport parameters in solid photo-polymer materials for 3D printing. Optics
Express. 2021;29(5):7568-7588. doi:10.1364/OE.406095
apa: Elek, O., Zhang, R., Sumin, D., Myszkowski, K., Bickel, B., Wilkie, A., … Weyrich,
T. (2021). Robust and practical measurement of volume transport parameters in
solid photo-polymer materials for 3D printing. Optics Express. The Optical
Society. https://doi.org/10.1364/OE.406095
chicago: Elek, Oskar, Ran Zhang, Denis Sumin, Karol Myszkowski, Bernd Bickel, Alexander
Wilkie, Jaroslav Křivánek, and Tim Weyrich. “Robust and Practical Measurement
of Volume Transport Parameters in Solid Photo-Polymer Materials for 3D Printing.”
Optics Express. The Optical Society, 2021. https://doi.org/10.1364/OE.406095.
ieee: O. Elek et al., “Robust and practical measurement of volume transport
parameters in solid photo-polymer materials for 3D printing,” Optics Express,
vol. 29, no. 5. The Optical Society, pp. 7568–7588, 2021.
ista: Elek O, Zhang R, Sumin D, Myszkowski K, Bickel B, Wilkie A, Křivánek J, Weyrich
T. 2021. Robust and practical measurement of volume transport parameters in solid
photo-polymer materials for 3D printing. Optics Express. 29(5), 7568–7588.
mla: Elek, Oskar, et al. “Robust and Practical Measurement of Volume Transport Parameters
in Solid Photo-Polymer Materials for 3D Printing.” Optics Express, vol.
29, no. 5, The Optical Society, 2021, pp. 7568–88, doi:10.1364/OE.406095.
short: O. Elek, R. Zhang, D. Sumin, K. Myszkowski, B. Bickel, A. Wilkie, J. Křivánek,
T. Weyrich, Optics Express 29 (2021) 7568–7588.
date_created: 2021-03-14T23:01:33Z
date_published: 2021-03-01T00:00:00Z
date_updated: 2025-03-31T15:58:16Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1364/OE.406095
ec_funded: 1
external_id:
isi:
- '000624968100103'
file:
- access_level: open_access
checksum: a9697ad83136c19ad87e46aa2db63cfd
content_type: application/pdf
creator: dernst
date_created: 2021-03-22T08:15:28Z
date_updated: 2021-03-22T08:15:28Z
file_id: '9269'
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relation: main_file
success: 1
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intvolume: ' 29'
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issue: '5'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 7568-7588
project:
- _id: 2508E324-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '642841'
name: Distributed 3D Object Design
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication: Optics Express
publication_identifier:
eissn:
- 1094-4087
publication_status: published
publisher: The Optical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Robust and practical measurement of volume transport parameters in solid photo-polymer
materials for 3D printing
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 29
year: '2021'
...
---
_id: '9376'
abstract:
- lang: eng
text: This paper presents a method for designing planar multistable compliant structures.
Given a sequence of desired stable states and the corresponding poses of the structure,
we identify the topology and geometric realization of a mechanism—consisting of
bars and joints—that is able to physically reproduce the desired multistable behavior.
In order to solve this problem efficiently, we build on insights from minimally
rigid graph theory to identify simple but effective topologies for the mechanism.
We then optimize its geometric parameters, such as joint positions and bar lengths,
to obtain correct transitions between the given poses. Simultaneously, we ensure
adequate stability of each pose based on an effective approximate error metric
related to the elastic energy Hessian of the bars in the mechanism. As demonstrated
by our results, we obtain functional multistable mechanisms of manageable complexity
that can be fabricated using 3D printing. Further, we evaluated the effectiveness
of our method on a large number of examples in the simulation and fabricated several
physical prototypes.
acknowledged_ssus:
- _id: M-Shop
acknowledgement: 'We would like to thank everyone who contributed to this paper, the
authors of artworks for all the examples, including @macrovec-tor_official and Wikimedia
for the FLAG semaphore, and @pikisuper-star for the FIGURINE. The photos of iconic
poses in the teaser were supplied by (from left to right): Mike Hewitt/Olympics
Day 8 - Athletics/Gettty Images, Oneinchpunch/Basketball player training on acourt
in New york city/Shutterstock, and Andrew Redington/TigerWoods/Getty Images. We
also want to express our gratitude to Christian Hafner for insightful discussions,
the IST Austria machine shop SSU, all proof-readers, and anonymous reviewers. This
project has received funding from the European Union’s Horizon 2020 research and
innovation programme, under the Marie Skłodowska-Curie grant agreement No 642841
(DISTRO), and under the European Research Council grant agreement No 715767 (MATERIALIZABLE).'
article_number: '186'
article_processing_charge: No
article_type: original
author:
- first_name: Ran
full_name: Zhang, Ran
id: 4DDBCEB0-F248-11E8-B48F-1D18A9856A87
last_name: Zhang
orcid: 0000-0002-3808-281X
- first_name: Thomas
full_name: Auzinger, Thomas
id: 4718F954-F248-11E8-B48F-1D18A9856A87
last_name: Auzinger
orcid: 0000-0002-1546-3265
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
citation:
ama: Zhang R, Auzinger T, Bickel B. Computational design of planar multistable compliant
structures. ACM Transactions on Graphics. 2021;40(5). doi:10.1145/3453477
apa: Zhang, R., Auzinger, T., & Bickel, B. (2021). Computational design of planar
multistable compliant structures. ACM Transactions on Graphics. Association
for Computing Machinery. https://doi.org/10.1145/3453477
chicago: Zhang, Ran, Thomas Auzinger, and Bernd Bickel. “Computational Design of
Planar Multistable Compliant Structures.” ACM Transactions on Graphics.
Association for Computing Machinery, 2021. https://doi.org/10.1145/3453477.
ieee: R. Zhang, T. Auzinger, and B. Bickel, “Computational design of planar multistable
compliant structures,” ACM Transactions on Graphics, vol. 40, no. 5. Association
for Computing Machinery, 2021.
ista: Zhang R, Auzinger T, Bickel B. 2021. Computational design of planar multistable
compliant structures. ACM Transactions on Graphics. 40(5), 186.
mla: Zhang, Ran, et al. “Computational Design of Planar Multistable Compliant Structures.”
ACM Transactions on Graphics, vol. 40, no. 5, 186, Association for Computing
Machinery, 2021, doi:10.1145/3453477.
short: R. Zhang, T. Auzinger, B. Bickel, ACM Transactions on Graphics 40 (2021).
date_created: 2021-05-08T17:37:08Z
date_published: 2021-10-08T00:00:00Z
date_updated: 2025-03-31T15:58:16Z
day: '08'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3453477
ec_funded: 1
external_id:
isi:
- '000752079300003'
file:
- access_level: open_access
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content_type: application/pdf
creator: bbickel
date_created: 2021-05-08T17:36:59Z
date_updated: 2021-05-08T17:36:59Z
file_id: '9377'
file_name: Multistable-authorversion.pdf
file_size: 18926557
relation: main_file
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checksum: 3b6e874e30bfa1bfc3ad3498710145a1
content_type: video/mp4
creator: bbickel
date_created: 2021-05-08T17:38:22Z
date_updated: 2021-05-08T17:38:22Z
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date_created: 2021-12-17T08:13:51Z
date_updated: 2021-12-17T08:13:51Z
description: This document provides additional results and analyzes the robustness
and limitations of our approach.
file_id: '10562'
file_name: multistable-supplementary material.pdf
file_size: 3367072
relation: supplementary_material
title: Supplementary Material for “Computational Design of Planar Multistable Compliant
Structures”
file_date_updated: 2021-12-17T08:13:51Z
has_accepted_license: '1'
intvolume: ' 40'
isi: 1
issue: '5'
keyword:
- multistability
- mechanism
- computational design
- rigidity
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
project:
- _id: 2508E324-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '642841'
name: Distributed 3D Object Design
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- 1557-7368
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Computational design of planar multistable compliant structures
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type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 40
year: '2021'
...
---
_id: '9408'
abstract:
- lang: eng
text: We present a computational design system that assists users to model, optimize,
and fabricate quad-robots with soft skins. Our system addresses the challenging
task of predicting their physical behavior by fully integrating the multibody
dynamics of the mechanical skeleton and the elastic behavior of the soft skin.
The developed motion control strategy uses an alternating optimization scheme
to avoid expensive full space time-optimization, interleaving space-time optimization
for the skeleton, and frame-by-frame optimization for the full dynamics. The output
are motor torques to drive the robot to achieve a user prescribed motion trajectory.
We also provide a collection of convenient engineering tools and empirical manufacturing
guidance to support the fabrication of the designed quad-robot. We validate the
feasibility of designs generated with our system through physics simulations and
with a physically-fabricated prototype.
acknowledgement: The authors would like to thank anonymous reviewers for their constructive
comments. Weiwei Xu is partially supported by Zhejiang Lab. Yin Yang is partially
spported by NSF under Grant Nos. CHS 1845024 and 1717972. Weiwei Xu and Hujun Bao
are supported by Fundamental Research Funds for the Central Universities. This project
has received funding from the European Research Council (ERC) under the European
Unions Horizon 2020 research and innovation programme (Grant agreement No 715767).
article_number: 2881-2895
article_processing_charge: No
author:
- first_name: Xudong
full_name: Feng, Xudong
last_name: Feng
- first_name: Jiafeng
full_name: Liu, Jiafeng
last_name: Liu
- first_name: Huamin
full_name: Wang, Huamin
last_name: Wang
- first_name: Yin
full_name: Yang, Yin
last_name: Yang
- first_name: Hujun
full_name: Bao, Hujun
last_name: Bao
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Weiwei
full_name: Xu, Weiwei
last_name: Xu
citation:
ama: Feng X, Liu J, Wang H, et al. Computational design of skinned Quad-Robots.
IEEE Transactions on Visualization and Computer Graphics. 2021;27(6). doi:10.1109/TVCG.2019.2957218
apa: Feng, X., Liu, J., Wang, H., Yang, Y., Bao, H., Bickel, B., & Xu, W. (2021).
Computational design of skinned Quad-Robots. IEEE Transactions on Visualization
and Computer Graphics. IEEE. https://doi.org/10.1109/TVCG.2019.2957218
chicago: Feng, Xudong, Jiafeng Liu, Huamin Wang, Yin Yang, Hujun Bao, Bernd Bickel,
and Weiwei Xu. “Computational Design of Skinned Quad-Robots.” IEEE Transactions
on Visualization and Computer Graphics. IEEE, 2021. https://doi.org/10.1109/TVCG.2019.2957218.
ieee: X. Feng et al., “Computational design of skinned Quad-Robots,” IEEE
Transactions on Visualization and Computer Graphics, vol. 27, no. 6. IEEE,
2021.
ista: Feng X, Liu J, Wang H, Yang Y, Bao H, Bickel B, Xu W. 2021. Computational
design of skinned Quad-Robots. IEEE Transactions on Visualization and Computer
Graphics. 27(6), 2881–2895.
mla: Feng, Xudong, et al. “Computational Design of Skinned Quad-Robots.” IEEE
Transactions on Visualization and Computer Graphics, vol. 27, no. 6, 2881–2895,
IEEE, 2021, doi:10.1109/TVCG.2019.2957218.
short: X. Feng, J. Liu, H. Wang, Y. Yang, H. Bao, B. Bickel, W. Xu, IEEE Transactions
on Visualization and Computer Graphics 27 (2021).
date_created: 2021-05-23T22:01:42Z
date_published: 2021-06-01T00:00:00Z
date_updated: 2025-07-10T12:01:44Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1109/TVCG.2019.2957218
ec_funded: 1
external_id:
isi:
- '000649620700009'
pmid:
- '31804937'
file:
- access_level: open_access
checksum: a78e6ac94e33ade4ffaea66943d5f7dc
content_type: application/pdf
creator: kschuh
date_created: 2021-05-25T15:08:49Z
date_updated: 2021-05-25T15:08:49Z
file_id: '9427'
file_name: 2021_TVCG_Feng.pdf
file_size: 6183002
relation: main_file
success: 1
file_date_updated: 2021-05-25T15:08:49Z
has_accepted_license: '1'
intvolume: ' 27'
isi: 1
issue: '6'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication: IEEE Transactions on Visualization and Computer Graphics
publication_identifier:
eissn:
- 1077-2626
issn:
- 1941-0506
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Computational design of skinned Quad-Robots
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
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short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 27
year: '2021'
...
---
_id: '9547'
abstract:
- lang: eng
text: With the wider availability of full-color 3D printers, color-accurate 3D-print
preparation has received increased attention. A key challenge lies in the inherent
translucency of commonly used print materials that blurs out details of the color
texture. Previous work tries to compensate for these scattering effects through
strategic assignment of colored primary materials to printer voxels. To date,
the highest-quality approach uses iterative optimization that relies on computationally
expensive Monte Carlo light transport simulation to predict the surface appearance
from subsurface scattering within a given print material distribution; that optimization,
however, takes in the order of days on a single machine. In our work, we dramatically
speed up the process by replacing the light transport simulation with a data-driven
approach. Leveraging a deep neural network to predict the scattering within a
highly heterogeneous medium, our method performs around two orders of magnitude
faster than Monte Carlo rendering while yielding optimization results of similar
quality level. The network is based on an established method from atmospheric
cloud rendering, adapted to our domain and extended by a physically motivated
weight sharing scheme that substantially reduces the network size. We analyze
its performance in an end-to-end print preparation pipeline and compare quality
and runtime to alternative approaches, and demonstrate its generalization to unseen
geometry and material values. This for the first time enables full heterogenous
material optimization for 3D-print preparation within time frames in the order
of the actual printing time.
acknowledgement: We thank Sebastian Cucerca for processing and capturing the phys-cal
printouts. This work was supported by the Charles University grant SVV-260588 and
Czech Science Foundation grant 19-07626S. This project has received funding from
the European Union’s Horizon 2020 research and innovation programme, under the Marie
Skłodowska Curie grant agreements No 642841 (DISTRO) and No765911 (RealVision),
and under the European Research Council grant agreement No 715767 (MATERIALIZABLE).
article_processing_charge: No
article_type: original
author:
- first_name: Tobias
full_name: Rittig, Tobias
last_name: Rittig
- first_name: Denis
full_name: Sumin, Denis
last_name: Sumin
- first_name: Vahid
full_name: Babaei, Vahid
last_name: Babaei
- first_name: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Alexey
full_name: Voloboy, Alexey
last_name: Voloboy
- first_name: Alexander
full_name: Wilkie, Alexander
last_name: Wilkie
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Karol
full_name: Myszkowski, Karol
last_name: Myszkowski
- first_name: Tim
full_name: Weyrich, Tim
last_name: Weyrich
- first_name: Jaroslav
full_name: Křivánek, Jaroslav
last_name: Křivánek
citation:
ama: Rittig T, Sumin D, Babaei V, et al. Neural acceleration of scattering-aware
color 3D printing. Computer Graphics Forum. 2021;40(2):205-219. doi:10.1111/cgf.142626
apa: Rittig, T., Sumin, D., Babaei, V., Didyk, P., Voloboy, A., Wilkie, A., … Křivánek,
J. (2021). Neural acceleration of scattering-aware color 3D printing. Computer
Graphics Forum. Wiley. https://doi.org/10.1111/cgf.142626
chicago: Rittig, Tobias, Denis Sumin, Vahid Babaei, Piotr Didyk, Alexey Voloboy,
Alexander Wilkie, Bernd Bickel, Karol Myszkowski, Tim Weyrich, and Jaroslav Křivánek.
“Neural Acceleration of Scattering-Aware Color 3D Printing.” Computer Graphics
Forum. Wiley, 2021. https://doi.org/10.1111/cgf.142626.
ieee: T. Rittig et al., “Neural acceleration of scattering-aware color 3D
printing,” Computer Graphics Forum, vol. 40, no. 2. Wiley, pp. 205–219,
2021.
ista: Rittig T, Sumin D, Babaei V, Didyk P, Voloboy A, Wilkie A, Bickel B, Myszkowski
K, Weyrich T, Křivánek J. 2021. Neural acceleration of scattering-aware color
3D printing. Computer Graphics Forum. 40(2), 205–219.
mla: Rittig, Tobias, et al. “Neural Acceleration of Scattering-Aware Color 3D Printing.”
Computer Graphics Forum, vol. 40, no. 2, Wiley, 2021, pp. 205–19, doi:10.1111/cgf.142626.
short: T. Rittig, D. Sumin, V. Babaei, P. Didyk, A. Voloboy, A. Wilkie, B. Bickel,
K. Myszkowski, T. Weyrich, J. Křivánek, Computer Graphics Forum 40 (2021) 205–219.
date_created: 2021-06-13T22:01:32Z
date_published: 2021-05-01T00:00:00Z
date_updated: 2025-03-31T15:58:16Z
day: '01'
ddc:
- '004'
department:
- _id: BeBi
doi: 10.1111/cgf.142626
ec_funded: 1
external_id:
isi:
- '000657959600017'
file:
- access_level: open_access
checksum: 33271724215f54a75c39d2ed40f2c502
content_type: application/pdf
creator: bbickel
date_created: 2021-10-11T12:06:50Z
date_updated: 2021-10-11T12:06:50Z
file_id: '10120'
file_name: ScatteringAwareColor3DPrinting_authorVersion.pdf
file_size: 26026501
relation: main_file
success: 1
file_date_updated: 2021-10-11T12:06:50Z
has_accepted_license: '1'
intvolume: ' 40'
isi: 1
issue: '2'
language:
- iso: eng
month: '05'
oa: 1
oa_version: Submitted Version
page: 205-219
project:
- _id: 2508E324-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '642841'
name: Distributed 3D Object Design
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication: Computer Graphics Forum
publication_identifier:
eissn:
- 1467-8659
issn:
- 0167-7055
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: Neural acceleration of scattering-aware color 3D printing
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 40
year: '2021'
...
---
_id: '9819'
abstract:
- lang: eng
text: Photorealistic editing of head portraits is a challenging task as humans are
very sensitive to inconsistencies in faces. We present an approach for high-quality
intuitive editing of the camera viewpoint and scene illumination (parameterised
with an environment map) in a portrait image. This requires our method to capture
and control the full reflectance field of the person in the image. Most editing
approaches rely on supervised learning using training data captured with setups
such as light and camera stages. Such datasets are expensive to acquire, not readily
available and do not capture all the rich variations of in-the-wild portrait images.
In addition, most supervised approaches only focus on relighting, and do not allow
camera viewpoint editing. Thus, they only capture and control a subset of the
reflectance field. Recently, portrait editing has been demonstrated by operating
in the generative model space of StyleGAN. While such approaches do not require
direct supervision, there is a significant loss of quality when compared to the
supervised approaches. In this paper, we present a method which learns from limited
supervised training data. The training images only include people in a fixed neutral
expression with eyes closed, without much hair or background variations. Each
person is captured under 150 one-light-at-a-time conditions and under 8 camera
poses. Instead of training directly in the image space, we design a supervised
problem which learns transformations in the latent space of StyleGAN. This combines
the best of supervised learning and generative adversarial modeling. We show that
the StyleGAN prior allows for generalisation to different expressions, hairstyles
and backgrounds. This produces high-quality photorealistic results for in-the-wild
images and significantly outperforms existing methods. Our approach can edit the
illumination and pose simultaneously, and runs at interactive rates.
acknowledgement: This work was supported by the ERC Consolidator Grant 4DReply (770784).
We also acknowledge support from Technicolor and InterDigital. We thank Tiancheng
Sun for kindly helping us with the comparisons with Sun et al. [2019].
article_number: '44'
article_processing_charge: Yes (in subscription journal)
article_type: original
arxiv: 1
author:
- first_name: B. R.
full_name: Mallikarjun, B. R.
last_name: Mallikarjun
- first_name: Ayush
full_name: Tewari, Ayush
last_name: Tewari
- first_name: Abdallah
full_name: Dib, Abdallah
last_name: Dib
- first_name: Tim
full_name: Weyrich, Tim
last_name: Weyrich
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Hans Peter
full_name: Seidel, Hans Peter
last_name: Seidel
- first_name: Hanspeter
full_name: Pfister, Hanspeter
last_name: Pfister
- first_name: Wojciech
full_name: Matusik, Wojciech
last_name: Matusik
- first_name: Louis
full_name: Chevallier, Louis
last_name: Chevallier
- first_name: Mohamed A.
full_name: Elgharib, Mohamed A.
last_name: Elgharib
- first_name: Christian
full_name: Theobalt, Christian
last_name: Theobalt
citation:
ama: 'Mallikarjun BR, Tewari A, Dib A, et al. PhotoApp: Photorealistic appearance
editing of head portraits. ACM Transactions on Graphics. 2021;40(4). doi:10.1145/3450626.3459765'
apa: 'Mallikarjun, B. R., Tewari, A., Dib, A., Weyrich, T., Bickel, B., Seidel,
H. P., … Theobalt, C. (2021). PhotoApp: Photorealistic appearance editing of head
portraits. ACM Transactions on Graphics. Association for Computing Machinery.
https://doi.org/10.1145/3450626.3459765'
chicago: 'Mallikarjun, B. R., Ayush Tewari, Abdallah Dib, Tim Weyrich, Bernd Bickel,
Hans Peter Seidel, Hanspeter Pfister, et al. “PhotoApp: Photorealistic Appearance
Editing of Head Portraits.” ACM Transactions on Graphics. Association for
Computing Machinery, 2021. https://doi.org/10.1145/3450626.3459765.'
ieee: 'B. R. Mallikarjun et al., “PhotoApp: Photorealistic appearance editing
of head portraits,” ACM Transactions on Graphics, vol. 40, no. 4. Association
for Computing Machinery, 2021.'
ista: 'Mallikarjun BR, Tewari A, Dib A, Weyrich T, Bickel B, Seidel HP, Pfister
H, Matusik W, Chevallier L, Elgharib MA, Theobalt C. 2021. PhotoApp: Photorealistic
appearance editing of head portraits. ACM Transactions on Graphics. 40(4), 44.'
mla: 'Mallikarjun, B. R., et al. “PhotoApp: Photorealistic Appearance Editing of
Head Portraits.” ACM Transactions on Graphics, vol. 40, no. 4, 44, Association
for Computing Machinery, 2021, doi:10.1145/3450626.3459765.'
short: B.R. Mallikarjun, A. Tewari, A. Dib, T. Weyrich, B. Bickel, H.P. Seidel,
H. Pfister, W. Matusik, L. Chevallier, M.A. Elgharib, C. Theobalt, ACM Transactions
on Graphics 40 (2021).
date_created: 2021-08-08T22:01:27Z
date_published: 2021-08-01T00:00:00Z
date_updated: 2026-04-16T08:19:58Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3450626.3459765
external_id:
arxiv:
- '2103.07658'
isi:
- '000674930900011'
file:
- access_level: open_access
checksum: 51b61b7e5c175e2d7ed8fa3b35f7525a
content_type: application/pdf
creator: asandaue
date_created: 2021-08-09T11:41:50Z
date_updated: 2021-08-09T11:41:50Z
file_id: '9834'
file_name: 2021_ACMTransactionsOnGraphics_Mallikarjun.pdf
file_size: 49840741
relation: main_file
success: 1
file_date_updated: 2021-08-09T11:41:50Z
has_accepted_license: '1'
intvolume: ' 40'
isi: 1
issue: '4'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- 1557-7368
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'PhotoApp: Photorealistic appearance editing of head portraits'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 40
year: '2021'
...
---
_id: '9820'
abstract:
- lang: eng
text: Material appearance hinges on material reflectance properties but also surface
geometry and illumination. The unlimited number of potential combinations between
these factors makes understanding and predicting material appearance a very challenging
task. In this work, we collect a large-scale dataset of perceptual ratings of
appearance attributes with more than 215,680 responses for 42,120 distinct combinations
of material, shape, and illumination. The goal of this dataset is twofold. First,
we analyze for the first time the effects of illumination and geometry in material
perception across such a large collection of varied appearances. We connect our
findings to those of the literature, discussing how previous knowledge generalizes
across very diverse materials, shapes, and illuminations. Second, we use the collected
dataset to train a deep learning architecture for predicting perceptual attributes
that correlate with human judgments. We demonstrate the consistent and robust
behavior of our predictor in various challenging scenarios, which, for the first
time, enables estimating perceived material attributes from general 2D images.
Since our predictor relies on the final appearance in an image, it can compare
appearance properties across different geometries and illumination conditions.
Finally, we demonstrate several applications that use our predictor, including
appearance reproduction using 3D printing, BRDF editing by integrating our predictor
in a differentiable renderer, illumination design, or material recommendations
for scene design.
acknowledgement: This project has received funding from the European Union’s Horizon
2020 research and innovation programme under the Marie Skłodowska-Curie, grant agreement
Nº 765911 (RealVision) and from the European Research Council (ERC), grant agreement
Nº 804226 (PERDY).
article_number: '125'
article_processing_charge: No
article_type: original
author:
- first_name: Ana
full_name: Serrano, Ana
last_name: Serrano
- first_name: Bin
full_name: Chen, Bin
last_name: Chen
- first_name: Chao
full_name: Wang, Chao
last_name: Wang
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
orcid: 0000-0002-5062-4474
- first_name: Hans Peter
full_name: Seidel, Hans Peter
last_name: Seidel
- first_name: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Karol
full_name: Myszkowski, Karol
last_name: Myszkowski
citation:
ama: 'Serrano A, Chen B, Wang C, et al. The effect of shape and illumination on
material perception: Model and applications. ACM Transactions on Graphics.
2021;40(4). doi:10.1145/3450626.3459813'
apa: 'Serrano, A., Chen, B., Wang, C., Piovarci, M., Seidel, H. P., Didyk, P., &
Myszkowski, K. (2021). The effect of shape and illumination on material perception:
Model and applications. ACM Transactions on Graphics. Association for Computing
Machinery. https://doi.org/10.1145/3450626.3459813'
chicago: 'Serrano, Ana, Bin Chen, Chao Wang, Michael Piovarci, Hans Peter Seidel,
Piotr Didyk, and Karol Myszkowski. “The Effect of Shape and Illumination on Material
Perception: Model and Applications.” ACM Transactions on Graphics. Association
for Computing Machinery, 2021. https://doi.org/10.1145/3450626.3459813.'
ieee: 'A. Serrano et al., “The effect of shape and illumination on material
perception: Model and applications,” ACM Transactions on Graphics, vol.
40, no. 4. Association for Computing Machinery, 2021.'
ista: 'Serrano A, Chen B, Wang C, Piovarci M, Seidel HP, Didyk P, Myszkowski K.
2021. The effect of shape and illumination on material perception: Model and applications.
ACM Transactions on Graphics. 40(4), 125.'
mla: 'Serrano, Ana, et al. “The Effect of Shape and Illumination on Material Perception:
Model and Applications.” ACM Transactions on Graphics, vol. 40, no. 4,
125, Association for Computing Machinery, 2021, doi:10.1145/3450626.3459813.'
short: A. Serrano, B. Chen, C. Wang, M. Piovarci, H.P. Seidel, P. Didyk, K. Myszkowski,
ACM Transactions on Graphics 40 (2021).
date_created: 2021-08-08T22:01:28Z
date_published: 2021-08-01T00:00:00Z
date_updated: 2026-04-16T08:20:28Z
day: '01'
department:
- _id: BeBi
doi: 10.1145/3450626.3459813
external_id:
isi:
- '000674930900090'
intvolume: ' 40'
isi: 1
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://zaguan.unizar.es/record/110704/files/texto_completo.pdf
month: '08'
oa: 1
oa_version: Submitted Version
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- 1557-7368
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'The effect of shape and illumination on material perception: Model and applications'
type: journal_article
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 40
year: '2021'
...
---
_id: '9957'
abstract:
- lang: eng
text: The reflectance field of a face describes the reflectance properties responsible
for complex lighting effects including diffuse, specular, inter-reflection and
self shadowing. Most existing methods for estimating the face reflectance from
a monocular image assume faces to be diffuse with very few approaches adding a
specular component. This still leaves out important perceptual aspects of reflectance
as higher-order global illumination effects and self-shadowing are not modeled.
We present a new neural representation for face reflectance where we can estimate
all components of the reflectance responsible for the final appearance from a
single monocular image. Instead of modeling each component of the reflectance
separately using parametric models, our neural representation allows us to generate
a basis set of faces in a geometric deformation-invariant space, parameterized
by the input light direction, viewpoint and face geometry. We learn to reconstruct
this reflectance field of a face just from a monocular image, which can be used
to render the face from any viewpoint in any light condition. Our method is trained
on a light-stage training dataset, which captures 300 people illuminated with
150 light conditions from 8 viewpoints. We show that our method outperforms existing
monocular reflectance reconstruction methods, in terms of photorealism due to
better capturing of physical premitives, such as sub-surface scattering, specularities,
self-shadows and other higher-order effects.
acknowledgement: "We thank Tarun Yenamandra and Duarte David for helping us with the
comparisons. This work was supported by the\r\nERC Consolidator Grant 4DReply (770784).
We also acknowledge support from InterDigital."
article_processing_charge: No
arxiv: 1
author:
- first_name: Mallikarjun
full_name: B R, Mallikarjun
last_name: B R
- first_name: Ayush
full_name: Tewari, Ayush
last_name: Tewari
- first_name: Tae-Hyun
full_name: Oh, Tae-Hyun
last_name: Oh
- first_name: Tim
full_name: Weyrich, Tim
last_name: Weyrich
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Hans-Peter
full_name: Seidel, Hans-Peter
last_name: Seidel
- first_name: Hanspeter
full_name: Pfister, Hanspeter
last_name: Pfister
- first_name: Wojciech
full_name: Matusik, Wojciech
last_name: Matusik
- first_name: Mohamed
full_name: Elgharib, Mohamed
last_name: Elgharib
- first_name: Christian
full_name: Theobalt, Christian
last_name: Theobalt
citation:
ama: 'B R M, Tewari A, Oh T-H, et al. Monocular reconstruction of neural face reflectance
fields. In: Proceedings of the IEEE Computer Society Conference on Computer
Vision and Pattern Recognition. IEEE; 2021:4791-4800. doi:10.1109/CVPR46437.2021.00476'
apa: 'B R, M., Tewari, A., Oh, T.-H., Weyrich, T., Bickel, B., Seidel, H.-P., …
Theobalt, C. (2021). Monocular reconstruction of neural face reflectance fields.
In Proceedings of the IEEE Computer Society Conference on Computer Vision and
Pattern Recognition (pp. 4791–4800). Nashville, TN, United States; Virtual:
IEEE. https://doi.org/10.1109/CVPR46437.2021.00476'
chicago: B R, Mallikarjun, Ayush Tewari, Tae-Hyun Oh, Tim Weyrich, Bernd Bickel,
Hans-Peter Seidel, Hanspeter Pfister, Wojciech Matusik, Mohamed Elgharib, and
Christian Theobalt. “Monocular Reconstruction of Neural Face Reflectance Fields.”
In Proceedings of the IEEE Computer Society Conference on Computer Vision and
Pattern Recognition, 4791–4800. IEEE, 2021. https://doi.org/10.1109/CVPR46437.2021.00476.
ieee: M. B R et al., “Monocular reconstruction of neural face reflectance
fields,” in Proceedings of the IEEE Computer Society Conference on Computer
Vision and Pattern Recognition, Nashville, TN, United States; Virtual, 2021,
pp. 4791–4800.
ista: 'B R M, Tewari A, Oh T-H, Weyrich T, Bickel B, Seidel H-P, Pfister H, Matusik
W, Elgharib M, Theobalt C. 2021. Monocular reconstruction of neural face reflectance
fields. Proceedings of the IEEE Computer Society Conference on Computer Vision
and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition,
4791–4800.'
mla: B R, Mallikarjun, et al. “Monocular Reconstruction of Neural Face Reflectance
Fields.” Proceedings of the IEEE Computer Society Conference on Computer Vision
and Pattern Recognition, IEEE, 2021, pp. 4791–800, doi:10.1109/CVPR46437.2021.00476.
short: M. B R, A. Tewari, T.-H. Oh, T. Weyrich, B. Bickel, H.-P. Seidel, H. Pfister,
W. Matusik, M. Elgharib, C. Theobalt, in:, Proceedings of the IEEE Computer Society
Conference on Computer Vision and Pattern Recognition, IEEE, 2021, pp. 4791–4800.
conference:
end_date: 2021-06-25
location: Nashville, TN, United States; Virtual
name: 'CVPR: Conference on Computer Vision and Pattern Recognition'
start_date: 2021-06-20
date_created: 2021-08-24T06:03:00Z
date_published: 2021-09-01T00:00:00Z
date_updated: 2023-08-11T11:08:35Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1109/CVPR46437.2021.00476
external_id:
arxiv:
- '2008.10247'
isi:
- '000739917304096'
file:
- access_level: open_access
checksum: 961db0bde76dd87cf833930080bb9f38
content_type: application/pdf
creator: bbickel
date_created: 2021-08-24T06:02:15Z
date_updated: 2021-08-24T06:02:15Z
file_id: '9958'
file_name: R_Monocular_Reconstruction_of_Neural_Face_Reflectance_Fields_CVPR_2021_paper[1].pdf
file_size: 4746649
relation: main_file
file_date_updated: 2021-08-24T06:02:15Z
has_accepted_license: '1'
isi: 1
language:
- iso: eng
month: '09'
oa: 1
oa_version: Preprint
page: 4791-4800
publication: Proceedings of the IEEE Computer Society Conference on Computer Vision
and Pattern Recognition
publication_identifier:
isbn:
- 978-166544509-2
issn:
- 1063-6919
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Monocular reconstruction of neural face reflectance fields
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
year: '2021'
...
---
_id: '9817'
abstract:
- lang: eng
text: Elastic bending of initially flat slender elements allows the realization
and economic fabrication of intriguing curved shapes. In this work, we derive
an intuitive but rigorous geometric characterization of the design space of plane
elastic rods with variable stiffness. It enables designers to determine which
shapes are physically viable with active bending by visual inspection alone. Building
on these insights, we propose a method for efficiently designing the geometry
of a flat elastic rod that realizes a target equilibrium curve, which only requires
solving a linear program. We implement this method in an interactive computational
design tool that gives feedback about the feasibility of a design, and computes
the geometry of the structural elements necessary to realize it within an instant.
The tool also offers an iterative optimization routine that improves the fabricability
of a model while modifying it as little as possible. In addition, we use our geometric
characterization to derive an algorithm for analyzing and recovering the stability
of elastic curves that would otherwise snap out of their unstable equilibrium
shapes by buckling. We show the efficacy of our approach by designing and manufacturing
several physical models that are assembled from flat elements.
acknowledgement: "We thank the anonymous reviewers for their generous feedback, and
Michal Piovarči for his help in producing the supplemental video. This project has
received funding from the European Research Council (ERC) under the European Union’s
Horizon 2020 research and innovation programme (grant agreement No 715767).\r\n"
article_number: '126'
article_processing_charge: No
article_type: original
author:
- first_name: Christian
full_name: Hafner, Christian
id: 400429CC-F248-11E8-B48F-1D18A9856A87
last_name: Hafner
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
citation:
ama: Hafner C, Bickel B. The design space of plane elastic curves. ACM Transactions
on Graphics. 2021;40(4). doi:10.1145/3450626.3459800
apa: 'Hafner, C., & Bickel, B. (2021). The design space of plane elastic curves.
ACM Transactions on Graphics. Virtual: Association for Computing Machinery.
https://doi.org/10.1145/3450626.3459800'
chicago: Hafner, Christian, and Bernd Bickel. “The Design Space of Plane Elastic
Curves.” ACM Transactions on Graphics. Association for Computing Machinery,
2021. https://doi.org/10.1145/3450626.3459800.
ieee: C. Hafner and B. Bickel, “The design space of plane elastic curves,” ACM
Transactions on Graphics, vol. 40, no. 4. Association for Computing Machinery,
2021.
ista: Hafner C, Bickel B. 2021. The design space of plane elastic curves. ACM Transactions
on Graphics. 40(4), 126.
mla: Hafner, Christian, and Bernd Bickel. “The Design Space of Plane Elastic Curves.”
ACM Transactions on Graphics, vol. 40, no. 4, 126, Association for Computing
Machinery, 2021, doi:10.1145/3450626.3459800.
short: C. Hafner, B. Bickel, ACM Transactions on Graphics 40 (2021).
conference:
end_date: 2021-08-13
location: Virtual
name: 'SIGGRAF: Special Interest Group on Computer Graphics and Interactive Techniques'
start_date: 2021-08-09
date_created: 2021-08-08T22:01:26Z
date_published: 2021-07-19T00:00:00Z
date_updated: 2026-07-03T22:30:38Z
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- theory of computation
- computational geometry
- mathematics of computing
- mathematical optimization
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name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
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publication: ACM Transactions on Graphics
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publisher: Association for Computing Machinery
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title: The design space of plane elastic curves
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---
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abstract:
- lang: eng
text: "Fabrication of curved shells plays an important role in modern design, industry,
and science. Among their remarkable properties are, for example, aesthetics of
organic shapes, ability to evenly distribute loads, or efficient flow separation.
They find applications across vast length scales ranging from sky-scraper architecture
to microscopic devices. But, at\r\nthe same time, the design of curved shells
and their manufacturing process pose a variety of challenges. In this thesis,
they are addressed from several perspectives. In particular, this thesis presents
approaches based on the transformation of initially flat sheets into the target
curved surfaces. This involves problems of interactive design of shells with nontrivial
mechanical constraints, inverse design of complex structural materials, and data-driven
modeling of delicate and time-dependent physical properties. At the same time,
two newly-developed self-morphing mechanisms targeting flat-to-curved transformation
are presented.\r\nIn architecture, doubly curved surfaces can be realized as cold
bent glass panelizations. Originally flat glass panels are bent into frames and
remain stressed. This is a cost-efficient fabrication approach compared to hot
bending, when glass panels are shaped plastically. However such constructions
are prone to breaking during bending, and it is highly\r\nnontrivial to navigate
the design space, keeping the panels fabricable and aesthetically pleasing at
the same time. We introduce an interactive design system for cold bent glass façades,
while previously even offline optimization for such scenarios has not been sufficiently
developed. Our method is based on a deep learning approach providing quick\r\nand
high precision estimation of glass panel shape and stress while handling the shape\r\nmultimodality.\r\nFabrication
of smaller objects of scales below 1 m, can also greatly benefit from shaping
originally flat sheets. In this respect, we designed new self-morphing shell mechanisms
transforming from an initial flat state to a doubly curved state with high precision
and detail. Our so-called CurveUps demonstrate the encodement of the geometric
information\r\ninto the shell. Furthermore, we explored the frontiers of programmable
materials and showed how temporal information can additionally be encoded into
a flat shell. This allows prescribing deformation sequences for doubly curved
surfaces and, thus, facilitates self-collision avoidance enabling complex shapes
and functionalities otherwise impossible.\r\nBoth of these methods include inverse
design tools keeping the user in the design loop."
acknowledged_ssus:
- _id: M-Shop
- _id: ScienComp
acknowledgement: "During the work on this thesis, I received substantial support from
IST Austria’s scientific service units. A big thank you to Todor Asenov and other
Miba Machine Shop team members for their help with fabrication of experimental prototypes.
In addition, I would like to thank Scientific Computing team for the support with
high performance computing.\r\nFinancial support was provided by the European Research
Council (ERC) under grant agreement No 715767 - MATERIALIZABLE: Intelligent fabrication-oriented
Computational Design and Modeling, which I gratefully acknowledge."
alternative_title:
- ISTA Thesis
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author:
- first_name: Ruslan
full_name: Guseinov, Ruslan
id: 3AB45EE2-F248-11E8-B48F-1D18A9856A87
last_name: Guseinov
orcid: 0000-0001-9819-5077
citation:
ama: 'Guseinov R. Computational design of curved thin shells: From glass façades
to programmable matter. 2020. doi:10.15479/AT:ISTA:8366'
apa: 'Guseinov, R. (2020). Computational design of curved thin shells: From glass
façades to programmable matter. Institute of Science and Technology Austria.
https://doi.org/10.15479/AT:ISTA:8366'
chicago: 'Guseinov, Ruslan. “Computational Design of Curved Thin Shells: From Glass
Façades to Programmable Matter.” Institute of Science and Technology Austria,
2020. https://doi.org/10.15479/AT:ISTA:8366.'
ieee: 'R. Guseinov, “Computational design of curved thin shells: From glass façades
to programmable matter,” Institute of Science and Technology Austria, 2020.'
ista: 'Guseinov R. 2020. Computational design of curved thin shells: From glass
façades to programmable matter. Institute of Science and Technology Austria.'
mla: 'Guseinov, Ruslan. Computational Design of Curved Thin Shells: From Glass
Façades to Programmable Matter. Institute of Science and Technology Austria,
2020, doi:10.15479/AT:ISTA:8366.'
short: 'R. Guseinov, Computational Design of Curved Thin Shells: From Glass Façades
to Programmable Matter, Institute of Science and Technology Austria, 2020.'
corr_author: '1'
date_created: 2020-09-10T16:19:55Z
date_published: 2020-09-21T00:00:00Z
date_updated: 2026-04-08T07:25:22Z
day: '21'
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call_identifier: H2020
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- 978-3-99078-010-7
issn:
- 2663-337X
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supervisor:
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full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
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orcid: 0000-0001-6511-9385
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---
_id: '8375'
abstract:
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text: 'Supplementary movies showing the following sequences for spatio-temporarily
programmed shells: input geometry and actuation time landscape; comparison of
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author:
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orcid: 0000-0001-9819-5077
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from glass façades to programmable matter.” 2020. doi:10.15479/AT:ISTA:8375'
apa: 'Guseinov, R. (2020). Supplementary data for “Computational design of curved
thin shells: from glass façades to programmable matter.” Institute of Science
and Technology Austria. https://doi.org/10.15479/AT:ISTA:8375'
chicago: 'Guseinov, Ruslan. “Supplementary Data for ‘Computational Design of Curved
Thin Shells: From Glass Façades to Programmable Matter.’” Institute of Science
and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8375.'
ieee: 'R. Guseinov, “Supplementary data for ‘Computational design of curved thin
shells: from glass façades to programmable matter.’” Institute of Science and
Technology Austria, 2020.'
ista: 'Guseinov R. 2020. Supplementary data for ‘Computational design of curved
thin shells: from glass façades to programmable matter’, Institute of Science
and Technology Austria, 10.15479/AT:ISTA:8375.'
mla: 'Guseinov, Ruslan. Supplementary Data for “Computational Design of Curved
Thin Shells: From Glass Façades to Programmable Matter.” Institute of Science
and Technology Austria, 2020, doi:10.15479/AT:ISTA:8375.'
short: R. Guseinov, (2020).
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