Non-Deterministic Face Mask Removal Based On 3D Priors

• URL: http://arxiv.org/abs/2202.09856v1
• Date: Sun, 20 Feb 2022 16:27:44 GMT
• Title: Non-Deterministic Face Mask Removal Based On 3D Priors
• Authors: Xiangnan Yin and Liming Chen
• Abstract summary: The proposed approach integrates a multi-task 3D face reconstruction module with a face inpainting module. By gradually controlling the 3D shape parameters, our method generates high-quality dynamic inpainting results with different expressions and mouth movements.
• Score: 3.8502825594372703
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper presents a novel image inpainting framework for face mask removal. Although current methods have demonstrated their impressive ability in recovering damaged face images, they suffer from two main problems: the dependence on manually labeled missing regions and the deterministic result corresponding to each input. The proposed approach tackles these problems by integrating a multi-task 3D face reconstruction module with a face inpainting module. Given a masked face image, the former predicts a 3DMM-based reconstructed face together with a binary occlusion map, providing dense geometrical and textural priors that greatly facilitate the inpainting task of the latter. By gradually controlling the 3D shape parameters, our method generates high-quality dynamic inpainting results with different expressions and mouth movements. Qualitative and quantitative experiments verify the effectiveness of the proposed method.

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