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FlashNormal: Detailed Surface Normal Estimation from Flash and No-Flash Images
High-quality surface normal estimation is preferred for detailed surface shape recovery and image editing. Existing single image-based methods, though being a practical setup, often struggle to recover fine surface details and are sensitive to inherent shape-reflectance ambiguity. While photometric stereo achieves high-fidelity surface normal estimation from images under varying lights, its applicability is strictly limited by requiring a multi-illumination capture setup. To this end, we propose FlashNormal, a diffusion-based surface normal estimator from flash/no-flash image pairs. While reta
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-26T04:34:08.000Z
First collected: 2026-09-21T09:42:05.193Z. This is not the publication date.