A Unified Spatial-Angular Structured Light for Single-View Acquisition of Shape and Reflectance
Xianmin Xu, Yuxin Lin, Haoyang Zhou, Chong Zeng, Yaxin Yu, Kun Zhou, Hongzhi Wu
Abstract
We propose a unified structured light, consisting of an LED array and an LCD mask, for high-quality acquisition of both shape and reflectance from a single view. For geometry, one LED projects a set of learned mask patterns to accurately encode spatial information; the decoded results from multiple LEDs are then aggregated to produce a final depth map. For appearance, learned light patterns are cast through a transparent mask to efficiently probe angularlyvarying reflectance. Per-point BRDF parameters are differentiably optimized with respect to corresponding measurements, and stored in texture maps as the final reflectance. We establish a differentiable pipeline for the joint capture to automatically optimize both the mask and light patterns towards optimal acquisition quality. The effectiveness of our light is demonstrated with a wide variety of physical objects. Our results compare favorably with state-of-the-art techniques.
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Install the CLIlune papers fulltext 06460751-a292-450f-9648-d7e49e8c7882Cited by top-tier papers5
- TurboSL: Dense, Accurate and Fast 3D by Neural Inverse Structured LightParsa Mirdehghan, Maxx Wu, Wenzheng Chen, David B. Lindell et al.CVPR 2024 · 5 citations
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- Differentiable Adaptive 4D Structured Illumination for Joint Capture of Shape and ReflectanceHuakeng Ding, Yaowen Chen, Kun Zhou, Hongzhi WuCVPR 2026
- SPIDeRS: Structured Polarization for Invisible Depth and Reflectance SensingTomoki Ichikawa, Shohei Nobuhara, Ko NishinoCVPR 2024
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- Free-form scanning of non-planar appearance with neural trace photographyXiaohe Ma, Kaizhang Kang, Ruisheng Zhu, Hongzhi Wu et al.SIGGRAPH 2021 · 22 citations
- Differentiable Volumetric Rendering: Learning Implicit 3D Representations Without 3D SupervisionMichael Niemeyer, Lars M. Mescheder, Michael Oechsle, Andreas GeigerCVPR 2020
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