mlsanityData to 14 Oct 2026

Exploring 3D Face Reconstruction and Fusion Methods for Face Verification: A Case-Study in Video Surveillance

arXiv 2409.10481 ↗First posted 16 Sep 2024cs.CV cs.AIcited by 3

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Abstract (arXiv)

3D face reconstruction (3DFR) algorithms are based on specific assumptions tailored to distinct application scenarios. These assumptions limit their use when acquisition conditions, such as the subject's distance from the camera or the camera's characteristics, are different than expected, as typically happens in video surveillance. Additionally, 3DFR algorithms follow various strategies to address the reconstruction of a 3D shape from 2D data, such as statistical model fitting, photometric stereo, or deep learning. In the present study, we explore the application of three 3DFR algorithms representative of the SOTA, employing each one as the template set generator for a face verification system. The scores provided by each system are combined by score-level fusion. We show that the complementarity induced by different 3DFR algorithms improves performance when tests are conducted at never-seen-before distances from the camera and camera characteristics (cross-distance and cross-camera settings), thus encouraging further investigations on multiple 3DFR-based approaches.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 15 of its 43 references that are in the map. First posted on arXiv 16 Sep 2024.

Builds on

15 of 43 references.

References · 15

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3 more
  1. 2021Recent Advances in Deep Learning Techniques for Face Recognitioncited by 5
  2. 20233D Face Reconstruction for Forensic Recognition -- A Surveycited by 4
  3. 2018An Evaluation of Score Level Fusion Approaches for Fingerprint and Finger-vein Biometricscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025Exploiting Multiple Representations: 3D Face Biometrics Fusion with Application to Surveillancecited by 4
  2. 2025Comparison of Visual Trackers for Biomechanical Analysis of Runningcited by 2
  3. 2026VideoRun2D Demo: Markerless Body Tracking for Biomechanical Analysis of Runningcited by 0