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Computer Science > Computer Vision and Pattern Recognition

arXiv:2208.07142 (cs)
[Submitted on 15 Aug 2022]

Title:Perspective Reconstruction of Human Faces by Joint Mesh and Landmark Regression

Authors:Jia Guo, Jinke Yu, Alexandros Lattas, Jiankang Deng
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Abstract:Even though 3D face reconstruction has achieved impressive progress, most orthogonal projection-based face reconstruction methods can not achieve accurate and consistent reconstruction results when the face is very close to the camera due to the distortion under the perspective projection. In this paper, we propose to simultaneously reconstruct 3D face mesh in the world space and predict 2D face landmarks on the image plane to address the problem of perspective 3D face reconstruction. Based on the predicted 3D vertices and 2D landmarks, the 6DoF (6 Degrees of Freedom) face pose can be easily estimated by the PnP solver to represent perspective projection. Our approach achieves 1st place on the leader-board of the ECCV 2022 WCPA challenge and our model is visually robust under different identities, expressions and poses. The training code and models are released to facilitate future research.
Comments: ECCV 2022 WCPA Workshop Report (1st place)
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2208.07142 [cs.CV]
  (or arXiv:2208.07142v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2208.07142

Submission history

From: Jiankang Deng [view email]
[v1] Mon, 15 Aug 2022 12:32:20 UTC (9,595 KB)
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