FlashNormal: Detailed Surface Normal Estimation from Flash and No-Flash Images

• URL: http://arxiv.org/abs/2608.25360v1
• Date: Wed, 26 Aug 2026 04:34:08 GMT
• Title: FlashNormal: Detailed Surface Normal Estimation from Flash and No-Flash Images
• Abstract summary: High-quality surface normal estimation is preferred for detailed surface shape recovery and image editing.<n>Existing single image-based methods, though being a practical setup, often struggle to recover fine surface details.<n>We propose FlashNormal, a diffusion-based surface normal estimator from flash/no-flash image pairs.
• Score: 33.19867070000115
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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 retaining high practicability on modern smartphones, our proposal takes advantage of flash-induced shading variations, and leverages curvature-guided detail enhancement strategy, improving surface detail recovery and mitigating shape-reflectance ambiguity effectively. To evaluate our proposed method, we further present EvalFlash, the first real-world flash/no-flash evaluation dataset containing 20 objects aligned with ground-truth surface normals for quantitative benchmarking. Extensive experiments demonstrate the effectiveness of FlashNormal over state-of-the-art single image-based methods and show a significant out-performance over flash/no-flash-based normal estimation method on EvalFlash.

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