---
_id: '18244'
abstract:
- lang: eng
  text: Some face recognition methods are designed to utilize geometric information
    extracted from depth sensors to overcome the weaknesses of single-image based
    recognition technologies. However, the accurate acquisition of the depth profile
    is an expensive and challenging process. Here, we introduce a novel method that
    learns to recognize faces from stereo camera systems without the need to explicitly
    compute the facial surface or depth map. The raw face stereo images along with
    the location in the image from which the face is extracted allow the proposed
    CNN to improve the recognition task while avoiding the need to explicitly handle
    the geometric structure of the face. This way, we keep the simplicity and cost
    efficiency of identity authentication from a single image, while enjoying the
    benefits of geometric data without explicitly reconstructing it. We demonstrate
    that the suggested method outperforms both existing single-image and explicit
    depth based methods on largescale benchmarks, and even capable of recognize spoofing
    attacks. We also provide an ablation study that shows that the suggested method
    uses the face locations in the left and right images to encode informative features
    that improve the overall performance.
article_number: '9320359'
article_processing_charge: No
arxiv: 1
author:
- first_name: Amir
  full_name: Livne, Amir
  last_name: Livne
- first_name: Ziv
  full_name: Aviv, Ziv
  last_name: Aviv
- first_name: Shahaf
  full_name: Grofit, Shahaf
  last_name: Grofit
- first_name: Alexander
  full_name: Bronstein, Alexander
  id: 58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
  last_name: Bronstein
  orcid: 0000-0001-9699-8730
- first_name: Ron
  full_name: Kimmel, Ron
  last_name: Kimmel
citation:
  ama: 'Livne A, Aviv Z, Grofit S, Bronstein AM, Kimmel R. Do we need depth in state-uf-the-art
    face authentication? In: <i>2020 International Conference on 3D Vision (3DV)</i>.
    IEEE; 2021. doi:<a href="https://doi.org/10.1109/3dv50981.2020.00099">10.1109/3dv50981.2020.00099</a>'
  apa: 'Livne, A., Aviv, Z., Grofit, S., Bronstein, A. M., &#38; Kimmel, R. (2021).
    Do we need depth in state-uf-the-art face authentication? In <i>2020 International
    Conference on 3D Vision (3DV)</i>. Fukuoka, Japan: IEEE. <a href="https://doi.org/10.1109/3dv50981.2020.00099">https://doi.org/10.1109/3dv50981.2020.00099</a>'
  chicago: Livne, Amir, Ziv Aviv, Shahaf Grofit, Alex M. Bronstein, and Ron Kimmel.
    “Do We Need Depth in State-Uf-the-Art Face Authentication?” In <i>2020 International
    Conference on 3D Vision (3DV)</i>. IEEE, 2021. <a href="https://doi.org/10.1109/3dv50981.2020.00099">https://doi.org/10.1109/3dv50981.2020.00099</a>.
  ieee: A. Livne, Z. Aviv, S. Grofit, A. M. Bronstein, and R. Kimmel, “Do we need
    depth in state-uf-the-art face authentication?,” in <i>2020 International Conference
    on 3D Vision (3DV)</i>, Fukuoka, Japan, 2021.
  ista: Livne A, Aviv Z, Grofit S, Bronstein AM, Kimmel R. 2021. Do we need depth
    in state-uf-the-art face authentication? 2020 International Conference on 3D Vision
    (3DV). 8th International Conference on 3D Vision, 9320359.
  mla: Livne, Amir, et al. “Do We Need Depth in State-Uf-the-Art Face Authentication?”
    <i>2020 International Conference on 3D Vision (3DV)</i>, 9320359, IEEE, 2021,
    doi:<a href="https://doi.org/10.1109/3dv50981.2020.00099">10.1109/3dv50981.2020.00099</a>.
  short: A. Livne, Z. Aviv, S. Grofit, A.M. Bronstein, R. Kimmel, in:, 2020 International
    Conference on 3D Vision (3DV), IEEE, 2021.
conference:
  end_date: 2020-11-28
  location: Fukuoka, Japan
  name: 8th International Conference on 3D Vision
  start_date: 2020-11-25
date_created: 2024-10-08T13:04:02Z
date_published: 2021-01-19T00:00:00Z
date_updated: 2024-12-12T10:10:29Z
day: '19'
doi: 10.1109/3dv50981.2020.00099
extern: '1'
external_id:
  arxiv:
  - '2003.10895'
fulldoi: https://doi.org/10.1109/3dv50981.2020.00099
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.48550/arXiv.2003.10895
month: '01'
oa: 1
oa_version: Preprint
publication: 2020 International Conference on 3D Vision (3DV)
publication_identifier:
  eissn:
  - 2475-7888
  isbn:
  - '9781728181295'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Do we need depth in state-uf-the-art face authentication?
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2021'
...