Face Relighting with Geometrically Consistent Shadows
Andrew Z. Hou, Michel Sarkis, Ning Bi, Yiying Tong, Xiaoming Liu
Abstract
Most face relighting methods are able to handle diffuse shadows, but struggle to handle hard shadows, such as those cast by the nose. Methods that propose techniques for handling hard shadows often do not produce geometrically consistent shadows since they do not directly leverage the estimated face geometry while synthesizing them. We propose a novel differentiable algorithm for synthesizing hard shadows based on ray tracing, which we incorporate into training our face relighting model. Our proposed algorithm directly utilizes the estimated face geometry to synthesize geometrically consistent hard shadows. We demonstrate through quantitative and qualitative experiments on Multi-PIE and FFHQ that our method produces more geometrically consistent shadows than previous face relighting methods while also achieving state-of-the-art face relighting performance under directional lighting. In addition, we demonstrate that our differentiable hard shadow modeling improves the quality of the estimated face geometry over diffuse shading models.
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Install the CLIlune papers fulltext a9309812-356a-4e7c-9a3b-17ab822d5a64Cited by top-tier papers21
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- EmoTaG: Emotion-Aware Talking Head Synthesis on Gaussian Splatting with Few-Shot PersonalizationHaolan Xu, Keli Cheng, Lei Wang, Ning Bi et al.CVPR 2026 · 5 citations
Builds on13
- Soft Rasterizer: A Differentiable Renderer for Image-Based 3D ReasoningShichen Liu, Weikai Chen, Tianye Li, Hao LiICCV 2019 · 789 citations
- Deep Single-Image Portrait RelightingHao Zhou, Sunil Hadap, Kalyan Sunkavalli, David JacobsICCV 2019 · 247 citations
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- Portrait shadow manipulationXuaner Cecilia Zhang, Jonathan T. Barron, Yun-Ta Tsai, Rohit Pandey et al.SIGGRAPH 2020 · 104 citations
- Efficient and Differentiable Shadow Computation for Inverse ProblemsLinjie Lyu, Marc Habermann, Lingjie Liu, Mallikarjun B. R. et al.ICCV 2021 · 16 citations
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