Computer Science > Computer Vision and Pattern Recognition
[Submitted on 8 Jul 2020 (v1), last revised 13 Sep 2020 (this version, v2)]
Title:Adaptive 3D Face Reconstruction from a Single Image
View PDFAbstract:3D face reconstruction from a single image is a challenging problem, especially under partial occlusions and extreme poses. This is because the uncertainty of the estimated 2D landmarks will affect the quality of face reconstruction. In this paper, we propose a novel joint 2D and 3D optimization method to adaptively reconstruct 3D face shapes from a single image, which combines the depths of 3D landmarks to solve the uncertain detections of invisible landmarks. The strategy of our method involves two aspects: a coarse-to-fine pose estimation using both 2D and 3D landmarks, and an adaptive 2D and 3D re-weighting based on the refined pose parameter to recover accurate 3D faces. Experimental results on multiple datasets demonstrate that our method can generate high-quality reconstruction from a single color image and is robust for self-occlusion and large poses.
Submission history
From: Kun Li [view email][v1] Wed, 8 Jul 2020 09:35:26 UTC (3,087 KB)
[v2] Sun, 13 Sep 2020 07:29:24 UTC (3,030 KB)
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