用解析图引导重建被遮挡人脸，提升真实感与鲁棒性
Generative Face Parsing Map Guided 3D Face Reconstruction Under Occluded Scenes
- 基于关键点生成面部解析图，估计遮挡区域结构
- 在遮挡场景下重建的3D纹理更真实，保持五官拓扑关系
- 适用于真实复杂遮挡场景，对现有方法有明显改进
近年来，单视角3D人脸重建方法已能生成高质量模型，但多基于无遮挡输入。本文提出一种面向遮挡场景的3D人脸重建系统，通过关键点引导生成完整的面部解析图，估计遮挡区域的合理2D结构，并用于3D纹理构建。该方法确保输出具备合理的五官拓扑结构，如眼、鼻、口之间的相对位置关系。我们在多种通用3D人脸重建任务上进行了广泛实验，定性验证了所估结构的合理性。定量结果表明，本方法在遮挡场景下显著提升了3D重建的质量与鲁棒性，优于现有方法。
原文摘要 · Abstract (English)
Over the past few years, single-view 3D face reconstruction methods can produce beautiful 3D models. Nevertheless,the input of these works is unobstructed faces.We describe a system designed to reconstruct convincing face texture in the case of occlusion.Motivated by parsing facial features,we propose a complete face parsing map generation method guided by landmarks.We estimate the 2D face structure of the reasonable position of the occlusion area,which is used for the construction of 3D texture.An excellent anti-occlusion face reconstruction method should ensure the authenticity of the output,including the topological structure between the eyes,nose, and mouth. We extensively tested our method and its components, qualitatively demonstrating the rationality of our estimated facial structure. We conduct extensive experiments on general 3D face reconstruction tasks as concrete examples to demonstrate the method's superior regulation ability over existing methods often break down.We further provide numerous quantitative examples showing that our method advances both the quality and the robustness of 3D face reconstruction under occlusion scenes.
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