[{"scopus_import":"1","article_processing_charge":"No","day":"22","citation":{"chicago":"Sperl, Georg, Rosa M. Sánchez-Banderas, Manwen Li, Chris Wojtan, and Miguel A. Otaduy. “Estimation of Yarn-Level Simulation Models for Production Fabrics.” ACM Transactions on Graphics. Association for Computing Machinery, 2022. https://doi.org/10.1145/3528223.3530167.","mla":"Sperl, Georg, et al. “Estimation of Yarn-Level Simulation Models for Production Fabrics.” ACM Transactions on Graphics, vol. 41, no. 4, 65, Association for Computing Machinery, 2022, doi:10.1145/3528223.3530167.","short":"G. Sperl, R.M. Sánchez-Banderas, M. Li, C. Wojtan, M.A. Otaduy, ACM Transactions on Graphics 41 (2022).","ista":"Sperl G, Sánchez-Banderas RM, Li M, Wojtan C, Otaduy MA. 2022. Estimation of yarn-level simulation models for production fabrics. ACM Transactions on Graphics. 41(4), 65.","ieee":"G. Sperl, R. M. Sánchez-Banderas, M. Li, C. Wojtan, and M. A. Otaduy, “Estimation of yarn-level simulation models for production fabrics,” ACM Transactions on Graphics, vol. 41, no. 4. Association for Computing Machinery, 2022.","apa":"Sperl, G., Sánchez-Banderas, R. M., Li, M., Wojtan, C., & Otaduy, M. A. (2022). Estimation of yarn-level simulation models for production fabrics. ACM Transactions on Graphics. Association for Computing Machinery. https://doi.org/10.1145/3528223.3530167","ama":"Sperl G, Sánchez-Banderas RM, Li M, Wojtan C, Otaduy MA. Estimation of yarn-level simulation models for production fabrics. ACM Transactions on Graphics. 2022;41(4). doi:10.1145/3528223.3530167"},"publication":"ACM Transactions on Graphics","article_type":"original","date_published":"2022-07-22T00:00:00Z","type":"journal_article","issue":"4","abstract":[{"lang":"eng","text":"This paper introduces a methodology for inverse-modeling of yarn-level mechanics of cloth, based on the mechanical response of fabrics in the real world. We compiled a database from physical tests of several different knitted fabrics used in the textile industry. These data span different types of complex knit patterns, yarn compositions, and fabric finishes, and the results demonstrate diverse physical properties like stiffness, nonlinearity, and anisotropy.\r\n\r\nWe then develop a system for approximating these mechanical responses with yarn-level cloth simulation. To do so, we introduce an efficient pipeline for converting between fabric-level data and yarn-level simulation, including a novel swatch-level approximation for speeding up computation, and some small-but-necessary extensions to yarn-level models used in computer graphics. The dataset used for this paper can be found at http://mslab.es/projects/YarnLevelFabrics."}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"11736","intvolume":" 41","title":"Estimation of yarn-level simulation models for production fabrics","status":"public","oa_version":"Published Version","publication_identifier":{"issn":["0730-0301"],"eissn":["1557-7368"]},"month":"07","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1145/3528223.3530167"}],"external_id":{"isi":["000830989200114"]},"oa":1,"quality_controlled":"1","isi":1,"doi":"10.1145/3528223.3530167","language":[{"iso":"eng"}],"acknowledged_ssus":[{"_id":"ScienComp"}],"article_number":"65","year":"2022","acknowledgement":"We wish to thank the anonymous reviewers for their helpful comments. To develop this project, we were helped by many people both at Under Armour (Clay Dean, Randall Harward, Kyle Blakely, Craig Simile, Michael Seiz, Brooke Malone, Brittainy McFarland, Emilie Phan, Lindsey Kern, Courtney Oswald, Haley Barkley, Bob Chin, Adam Bayer, Connie Kwok, Marielle Newman, Nick Pence, Allison Hicks, Allison White, Candace Rubenstein, Jeremy Stangland, Fred Fagergren, Michael Mazzoleni, Nathaniel Berry, Manuel Frank) and SEDDI (Gabriel Cirio, Alejandro Rodríguez, Sofía Dominguez, Alicia Nicas, Elena Garcés, Daniel Rodríguez, David Pascual, Manuel Godoy, Sergio Suja, Sergio Ruiz, Roberto Condori, Alberto Martín, Graham Sullivan). We also thank the members of the Visual Computing Group at IST Austria and the Multimodal Simulation Lab at URJC for their feedback. This research was supported by the Scientific Service Units (SSU) of IST Austria through resources provided by Scientific Computing, and it was funded in part by the European Research Council (ERC Consolidator Grant 772738 TouchDesign).","department":[{"_id":"ChWo"}],"publisher":"Association for Computing Machinery","publication_status":"published","related_material":{"link":[{"relation":"press_release","description":"News on the ISTA website","url":"https://ista.ac.at/en/news/digital-yarn-real-socks/"}],"record":[{"status":"public","relation":"dissertation_contains","id":"12358"}]},"author":[{"id":"4DD40360-F248-11E8-B48F-1D18A9856A87","first_name":"Georg","last_name":"Sperl","full_name":"Sperl, Georg"},{"full_name":"Sánchez-Banderas, Rosa M.","first_name":"Rosa M.","last_name":"Sánchez-Banderas"},{"full_name":"Li, Manwen","last_name":"Li","first_name":"Manwen"},{"full_name":"Wojtan, Christopher J","last_name":"Wojtan","first_name":"Christopher J","orcid":"0000-0001-6646-5546","id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Otaduy","first_name":"Miguel A.","full_name":"Otaduy, Miguel A."}],"volume":41,"date_updated":"2023-08-03T12:38:30Z","date_created":"2022-08-07T22:01:58Z"},{"title":"Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting","status":"public","ddc":["000","620"],"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","_id":"12358","file":[{"access_level":"open_access","description":"This is the main PDF file of the thesis. File size: 105 MB","file_name":"thesis_gsperl.pdf","content_type":"application/pdf","file_size":104497530,"creator":"cchlebak","relation":"main_file","file_id":"12371","title":"Thesis","checksum":"083722acbb8115e52e3b0fdec6226769","date_created":"2023-01-25T12:04:41Z","date_updated":"2023-02-02T09:29:57Z"},{"date_updated":"2023-02-02T09:33:37Z","date_created":"2023-02-02T09:33:37Z","checksum":"511f82025e5fcb70bff4731d6896ca07","file_id":"12483","title":"Thesis (compressed 23MB)","relation":"main_file","creator":"cchlebak","content_type":"application/pdf","file_size":23183710,"description":"This version of the thesis uses stronger image compression for a smaller file size of 23MB.","file_name":"thesis_gsperl_compressed.pdf","access_level":"open_access"},{"date_updated":"2023-02-02T09:39:25Z","date_created":"2023-02-02T09:39:25Z","checksum":"ed4cb85225eedff761c25bddfc37a2ed","file_id":"12484","relation":"source_file","creator":"cchlebak","content_type":"application/x-zip-compressed","file_size":98382247,"file_name":"thesis-source.zip","access_level":"open_access"}],"oa_version":"Published Version","alternative_title":["ISTA Thesis"],"type":"dissertation","abstract":[{"lang":"eng","text":"The complex yarn structure of knitted and woven fabrics gives rise to both a mechanical and\r\nvisual complexity. The small-scale interactions of yarns colliding with and pulling on each\r\nother result in drastically different large-scale stretching and bending behavior, introducing\r\nanisotropy, curling, and more. While simulating cloth as individual yarns can reproduce this\r\ncomplexity and match the quality of real fabric, it may be too computationally expensive for\r\nlarge fabrics. On the other hand, continuum-based approaches do not need to discretize the\r\ncloth at a stitch-level, but it is non-trivial to find a material model that would replicate the\r\nlarge-scale behavior of yarn fabrics, and they discard the intricate visual detail. In this thesis,\r\nwe discuss three methods to try and bridge the gap between small-scale and large-scale yarn\r\nmechanics using numerical homogenization: fitting a continuum model to periodic yarn simulations, adding mechanics-aware yarn detail onto thin-shell simulations, and quantitatively\r\nfitting yarn parameters to physical measurements of real fabric.\r\nTo start, we present a method for animating yarn-level cloth effects using a thin-shell solver.\r\nWe first use a large number of periodic yarn-level simulations to build a model of the potential\r\nenergy density of the cloth, and then use it to compute forces in a thin-shell simulator. The\r\nresulting simulations faithfully reproduce expected effects like the stiffening of woven fabrics\r\nand the highly deformable nature and anisotropy of knitted fabrics at a fraction of the cost of\r\nfull yarn-level simulation.\r\nWhile our thin-shell simulations are able to capture large-scale yarn mechanics, they lack\r\nthe rich visual detail of yarn-level simulations. Therefore, we propose a method to animate\r\nyarn-level cloth geometry on top of an underlying deforming mesh in a mechanics-aware\r\nfashion in real time. Using triangle strains to interpolate precomputed yarn geometry, we are\r\nable to reproduce effects such as knit loops tightening under stretching at negligible cost.\r\nFinally, we introduce a methodology for inverse-modeling of yarn-level mechanics of cloth,\r\nbased on the mechanical response of fabrics in the real world. We compile a database from\r\nphysical tests of several knitted fabrics used in the textile industry spanning diverse physical\r\nproperties like stiffness, nonlinearity, and anisotropy. We then develop a system for approximating these mechanical responses with yarn-level cloth simulation, using homogenized\r\nshell models to speed up computation and adding some small-but-necessary extensions to\r\nyarn-level models used in computer graphics.\r\n"}],"page":"138","citation":{"ama":"Sperl G. Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting. 2022. doi:10.15479/at:ista:12103","ista":"Sperl G. 2022. Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting. Institute of Science and Technology Austria.","apa":"Sperl, G. (2022). Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:12103","ieee":"G. Sperl, “Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting,” Institute of Science and Technology Austria, 2022.","mla":"Sperl, Georg. Homogenizing Yarn Simulations: Large-Scale Mechanics, Small-Scale Detail, and Quantitative Fitting. Institute of Science and Technology Austria, 2022, doi:10.15479/at:ista:12103.","short":"G. Sperl, Homogenizing Yarn Simulations: Large-Scale Mechanics, Small-Scale Detail, and Quantitative Fitting, Institute of Science and Technology Austria, 2022.","chicago":"Sperl, Georg. “Homogenizing Yarn Simulations: Large-Scale Mechanics, Small-Scale Detail, and Quantitative Fitting.” Institute of Science and Technology Austria, 2022. https://doi.org/10.15479/at:ista:12103."},"date_published":"2022-09-22T00:00:00Z","day":"22","article_processing_charge":"No","has_accepted_license":"1","publication_status":"published","publisher":"Institute of Science and Technology Austria","department":[{"_id":"GradSch"},{"_id":"ChWo"}],"year":"2022","date_created":"2023-01-24T10:49:46Z","date_updated":"2024-02-28T12:57:46Z","author":[{"full_name":"Sperl, Georg","id":"4DD40360-F248-11E8-B48F-1D18A9856A87","first_name":"Georg","last_name":"Sperl"}],"related_material":{"record":[{"relation":"part_of_dissertation","status":"public","id":"11736"},{"id":"9818","status":"public","relation":"part_of_dissertation"},{"id":"8385","status":"public","relation":"part_of_dissertation"}]},"file_date_updated":"2023-02-02T09:39:25Z","ec_funded":1,"project":[{"grant_number":"638176","_id":"2533E772-B435-11E9-9278-68D0E5697425","name":"Efficient Simulation of Natural Phenomena at Extremely Large Scales","call_identifier":"H2020"}],"oa":1,"supervisor":[{"full_name":"Wojtan, Christopher J","orcid":"0000-0001-6646-5546","id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87","last_name":"Wojtan","first_name":"Christopher J"}],"degree_awarded":"PhD","acknowledged_ssus":[{"_id":"SSU"}],"language":[{"iso":"eng"}],"doi":"10.15479/at:ista:12103","month":"09","publication_identifier":{"isbn":["978-3-99078-020-6"],"issn":["2663-337X"]}},{"acknowledgement":"We wish to thank the anonymous reviewers and the members of the Visual Computing Group at IST Austria for their valuable feedback. We also thank Seddi Labs for providing the garment model with fold-over seams.\r\nThis research was supported by the Scientific Service Units (SSU) of IST Austria through resources provided by Scientific\r\nComputing. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 638176. Rahul Narain is supported by a Pankaj Gupta Young Faculty Fellowship and a gift from Adobe Inc.","year":"2021","publication_status":"published","department":[{"_id":"GradSch"},{"_id":"ChWo"}],"publisher":"Association for Computing Machinery","author":[{"full_name":"Sperl, Georg","first_name":"Georg","last_name":"Sperl","id":"4DD40360-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Narain, Rahul","last_name":"Narain","first_name":"Rahul"},{"full_name":"Wojtan, Christopher J","orcid":"0000-0001-6646-5546","id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87","last_name":"Wojtan","first_name":"Christopher J"}],"related_material":{"record":[{"id":"12358","relation":"dissertation_contains","status":"public"},{"status":"public","relation":"software","id":"9327"}],"link":[{"url":"https://ist.ac.at/en/news/knitting-virtual-yarn/","relation":"press_release","description":"News on IST Webpage"}]},"date_updated":"2023-08-10T14:24:36Z","date_created":"2021-08-08T22:01:27Z","volume":40,"article_number":"168","ec_funded":1,"external_id":{"isi":["000674930900132"]},"main_file_link":[{"url":"https://doi.org/10.1145/3450626.3459816","open_access":"1"}],"oa":1,"isi":1,"quality_controlled":"1","project":[{"grant_number":"638176","_id":"2533E772-B435-11E9-9278-68D0E5697425","name":"Efficient Simulation of Natural Phenomena at Extremely Large Scales","call_identifier":"H2020"}],"doi":"10.1145/3450626.3459816","acknowledged_ssus":[{"_id":"ScienComp"}],"language":[{"iso":"eng"}],"month":"08","publication_identifier":{"issn":["07300301"],"eissn":["15577368"]},"_id":"9818","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","status":"public","title":"Mechanics-aware deformation of yarn pattern geometry","intvolume":" 40","oa_version":"Published Version","type":"journal_article","abstract":[{"text":"Triangle mesh-based simulations are able to produce satisfying animations of knitted and woven cloth; however, they lack the rich geometric detail of yarn-level simulations. Naive texturing approaches do not consider yarn-level physics, while full yarn-level simulations may become prohibitively expensive for large garments. We propose a method to animate yarn-level cloth geometry on top of an underlying deforming mesh in a mechanics-aware fashion. Using triangle strains to interpolate precomputed yarn geometry, we are able to reproduce effects such as knit loops tightening under stretching. In combination with precomputed mesh animation or real-time mesh simulation, our method is able to animate yarn-level cloth in real-time at large scales.","lang":"eng"}],"issue":"4","publication":"ACM Transactions on Graphics","citation":{"short":"G. Sperl, R. Narain, C. Wojtan, ACM Transactions on Graphics 40 (2021).","mla":"Sperl, Georg, et al. “Mechanics-Aware Deformation of Yarn Pattern Geometry.” ACM Transactions on Graphics, vol. 40, no. 4, 168, Association for Computing Machinery, 2021, doi:10.1145/3450626.3459816.","chicago":"Sperl, Georg, Rahul Narain, and Chris Wojtan. “Mechanics-Aware Deformation of Yarn Pattern Geometry.” ACM Transactions on Graphics. Association for Computing Machinery, 2021. https://doi.org/10.1145/3450626.3459816.","ama":"Sperl G, Narain R, Wojtan C. Mechanics-aware deformation of yarn pattern geometry. ACM Transactions on Graphics. 2021;40(4). doi:10.1145/3450626.3459816","apa":"Sperl, G., Narain, R., & Wojtan, C. (2021). Mechanics-aware deformation of yarn pattern geometry. ACM Transactions on Graphics. Association for Computing Machinery. https://doi.org/10.1145/3450626.3459816","ieee":"G. Sperl, R. Narain, and C. 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Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data). IST Austria, 2021, doi:10.15479/AT:ISTA:9327.","short":"G. Sperl, R. Narain, C. Wojtan, (2021).","chicago":"Sperl, Georg, Rahul Narain, and Chris Wojtan. “Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data).” IST Austria, 2021. https://doi.org/10.15479/AT:ISTA:9327.","ama":"Sperl G, Narain R, Wojtan C. Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data). 2021. doi:10.15479/AT:ISTA:9327","ista":"Sperl G, Narain R, Wojtan C. 2021. Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data), IST Austria, 10.15479/AT:ISTA:9327.","ieee":"G. Sperl, R. Narain, and C. Wojtan, “Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data).” IST Austria, 2021.","apa":"Sperl, G., Narain, R., & Wojtan, C. (2021). Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data). IST Austria. https://doi.org/10.15479/AT:ISTA:9327"},"oa":1,"date_published":"2021-05-01T00:00:00Z","doi":"10.15479/AT:ISTA:9327"},{"date_published":"2020-07-08T00:00:00Z","article_type":"original","citation":{"chicago":"Sperl, Georg, Rahul Narain, and Chris Wojtan. “Homogenized Yarn-Level Cloth.” ACM Transactions on Graphics. Association for Computing Machinery, 2020. https://doi.org/10.1145/3386569.3392412.","short":"G. Sperl, R. Narain, C. Wojtan, ACM Transactions on Graphics 39 (2020).","mla":"Sperl, Georg, et al. “Homogenized Yarn-Level Cloth.” ACM Transactions on Graphics, vol. 39, no. 4, 48, Association for Computing Machinery, 2020, doi:10.1145/3386569.3392412.","apa":"Sperl, G., Narain, R., & Wojtan, C. (2020). Homogenized yarn-level cloth. ACM Transactions on Graphics. Association for Computing Machinery. https://doi.org/10.1145/3386569.3392412","ieee":"G. Sperl, R. Narain, and C. Wojtan, “Homogenized yarn-level cloth,” ACM Transactions on Graphics, vol. 39, no. 4. Association for Computing Machinery, 2020.","ista":"Sperl G, Narain R, Wojtan C. 2020. Homogenized yarn-level cloth. ACM Transactions on Graphics. 39(4), 48.","ama":"Sperl G, Narain R, Wojtan C. Homogenized yarn-level cloth. ACM Transactions on Graphics. 2020;39(4). doi:10.1145/3386569.3392412"},"publication":"ACM Transactions on Graphics","has_accepted_license":"1","article_processing_charge":"No","day":"08","scopus_import":"1","file":[{"checksum":"cf4c1d361c3196c4bd424520a5588205","success":1,"date_updated":"2020-11-23T09:01:22Z","date_created":"2020-11-23T09:01:22Z","relation":"main_file","file_id":"8794","content_type":"application/pdf","file_size":38922662,"creator":"dernst","access_level":"open_access","file_name":"2020_hylc_submitted.pdf"}],"oa_version":"Submitted Version","intvolume":" 39","ddc":["000"],"status":"public","title":"Homogenized yarn-level cloth","_id":"8385","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"4","abstract":[{"text":"We present a method for animating yarn-level cloth effects using a thin-shell solver. We accomplish this through numerical homogenization: we first use a large number of yarn-level simulations to build a model of the potential energy density of the cloth, and then use this energy density function to compute forces in a thin shell simulator. We model several yarn-based materials, including both woven and knitted fabrics. Our model faithfully reproduces expected effects like the stiffness of woven fabrics, and the highly deformable nature and anisotropy of knitted fabrics. Our approach does not require any real-world experiments nor measurements; because the method is based entirely on simulations, it can generate entirely new material models quickly, without the need for testing apparatuses or human intervention. We provide data-driven models of several woven and knitted fabrics, which can be used for efficient simulation with an off-the-shelf cloth solver.","lang":"eng"}],"type":"journal_article","language":[{"iso":"eng"}],"acknowledged_ssus":[{"_id":"ScienComp"}],"doi":"10.1145/3386569.3392412","project":[{"grant_number":"638176","_id":"2533E772-B435-11E9-9278-68D0E5697425","name":"Efficient Simulation of Natural Phenomena at Extremely Large Scales","call_identifier":"H2020"}],"quality_controlled":"1","isi":1,"external_id":{"isi":["000583700300021"]},"oa":1,"main_file_link":[{"url":"https://doi.org/10.1145/3386569.3392412","open_access":"1"}],"publication_identifier":{"eissn":["15577368"],"issn":["07300301"]},"month":"07","volume":39,"date_updated":"2024-02-28T12:57:47Z","date_created":"2020-09-13T22:01:18Z","related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"12358"}]},"author":[{"id":"4DD40360-F248-11E8-B48F-1D18A9856A87","first_name":"Georg","last_name":"Sperl","full_name":"Sperl, Georg"},{"first_name":"Rahul","last_name":"Narain","full_name":"Narain, Rahul"},{"full_name":"Wojtan, Christopher J","orcid":"0000-0001-6646-5546","id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87","last_name":"Wojtan","first_name":"Christopher J"}],"publisher":"Association for Computing Machinery","department":[{"_id":"ChWo"}],"publication_status":"published","acknowledgement":"We wish to thank the anonymous reviewers and the members of the Visual Computing Group at IST Austria for their valuable feedback. We also thank the creators of the Berkeley Garment Library [de Joya et al. 2012] for providing garment meshes, [Krishnamurthy and Levoy 1996] and [Turk and Levoy 1994] for the armadillo and bunny meshes, the creators of libWetCloth [Fei et al. 2018] for their implementation of discrete elastic rod forces, and Tomáš Skřivan for\r\ninspiring discussions and help with Mathematica code generation. This research was supported by the Scientific Service Units (SSU) of IST Austria through resources provided by Scientific Computing. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 638176. Rahul Narain is supported by a Pankaj Gupta Young Faculty Fellowship and a gift from Adobe Inc.","year":"2020","ec_funded":1,"file_date_updated":"2020-11-23T09:01:22Z","article_number":"48"},{"oa":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1611.07725"}],"external_id":{"isi":["000418371405066"]},"isi":1,"quality_controlled":"1","project":[{"name":"Lifelong Learning of Visual Scene Understanding","call_identifier":"FP7","grant_number":"308036","_id":"2532554C-B435-11E9-9278-68D0E5697425"}],"conference":{"end_date":"2017-07-26","start_date":"2017-07-21","location":"Honolulu, HA, United States","name":"CVPR: Computer Vision and Pattern Recognition"},"doi":"10.1109/CVPR.2017.587","language":[{"iso":"eng"}],"month":"04","publication_identifier":{"isbn":["978-153860457-1"]},"year":"2017","publication_status":"published","publisher":"IEEE","department":[{"_id":"ChLa"},{"_id":"ChWo"}],"author":[{"full_name":"Rebuffi, Sylvestre Alvise","last_name":"Rebuffi","first_name":"Sylvestre Alvise"},{"full_name":"Kolesnikov, Alexander","last_name":"Kolesnikov","first_name":"Alexander","id":"2D157DB6-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Sperl, Georg","first_name":"Georg","last_name":"Sperl","id":"4DD40360-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Lampert","first_name":"Christoph","orcid":"0000-0001-8622-7887","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","full_name":"Lampert, Christoph"}],"date_updated":"2023-09-22T09:51:58Z","date_created":"2018-12-11T11:49:37Z","volume":2017,"ec_funded":1,"publist_id":"6400","citation":{"ista":"Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. 2017. iCaRL: Incremental classifier and representation learning. CVPR: Computer Vision and Pattern Recognition vol. 2017, 5533–5542.","ieee":"S. A. Rebuffi, A. Kolesnikov, G. Sperl, and C. Lampert, “iCaRL: Incremental classifier and representation learning,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 5533–5542.","apa":"Rebuffi, S. A., Kolesnikov, A., Sperl, G., & Lampert, C. (2017). iCaRL: Incremental classifier and representation learning (Vol. 2017, pp. 5533–5542). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.587","ama":"Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. iCaRL: Incremental classifier and representation learning. In: Vol 2017. IEEE; 2017:5533-5542. doi:10.1109/CVPR.2017.587","chicago":"Rebuffi, Sylvestre Alvise, Alexander Kolesnikov, Georg Sperl, and Christoph Lampert. “ICaRL: Incremental Classifier and Representation Learning,” 2017:5533–42. IEEE, 2017. https://doi.org/10.1109/CVPR.2017.587.","mla":"Rebuffi, Sylvestre Alvise, et al. ICaRL: Incremental Classifier and Representation Learning. Vol. 2017, IEEE, 2017, pp. 5533–42, doi:10.1109/CVPR.2017.587.","short":"S.A. Rebuffi, A. Kolesnikov, G. Sperl, C. Lampert, in:, IEEE, 2017, pp. 5533–5542."},"page":"5533 - 5542","date_published":"2017-04-14T00:00:00Z","scopus_import":"1","day":"14","article_processing_charge":"No","_id":"998","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","status":"public","title":"iCaRL: Incremental classifier and representation learning","intvolume":" 2017","oa_version":"Submitted Version","type":"conference","abstract":[{"text":"A major open problem on the road to artificial intelligence is the development of incrementally learning systems that learn about more and more concepts over time from a stream of data. In this work, we introduce a new training strategy, iCaRL, that allows learning in such a class-incremental way: only the training data for a small number of classes has to be present at the same time and new classes can be added progressively. iCaRL learns strong classifiers and a data representation simultaneously. This distinguishes it from earlier works that were fundamentally limited to fixed data representations and therefore incompatible with deep learning architectures. We show by experiments on CIFAR-100 and ImageNet ILSVRC 2012 data that iCaRL can learn many classes incrementally over a long period of time where other strategies quickly fail. ","lang":"eng"}]}]