GLOW: Global Illumination-Aware Inverse Rendering of Indoor Scenes Captured with Dynamic Co-Located Light & Camera

• URL: http://arxiv.org/abs/2511.22857v1
• Date: Fri, 28 Nov 2025 03:24:12 GMT
• Title: GLOW: Global Illumination-Aware Inverse Rendering of Indoor Scenes Captured with Dynamic Co-Located Light & Camera
• Authors: Jiaye Wu, Saeed Hadadan, Geng Lin, Peihan Tu, Matthias Zwicker, David Jacobs, Roni Sengupta,
• Abstract summary: Inverse rendering of indoor scenes remains challenging due to the ambiguity between reflectance and lighting.<n>We present GLOW, a Global Illumination-aware Inverse Rendering framework designed to address these challenges.
• Score: 18.90141473604964
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Inverse rendering of indoor scenes remains challenging due to the ambiguity between reflectance and lighting, exacerbated by inter-reflections among multiple objects. While natural illumination-based methods struggle to resolve this ambiguity, co-located light-camera setups offer better disentanglement as lighting can be easily calibrated via Structure-from-Motion. However, such setups introduce additional complexities like strong inter-reflections, dynamic shadows, near-field lighting, and moving specular highlights, which existing approaches fail to handle. We present GLOW, a Global Illumination-aware Inverse Rendering framework designed to address these challenges. GLOW integrates a neural implicit surface representation with a neural radiance cache to approximate global illumination, jointly optimizing geometry and reflectance through carefully designed regularization and initialization. We then introduce a dynamic radiance cache that adapts to sharp lighting discontinuities from near-field motion, and a surface-angle-weighted radiometric loss to suppress specular artifacts common in flashlight captures. Experiments show that GLOW substantially outperforms prior methods in material reflectance estimation under both natural and co-located illumination.

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