InvRGB+L: Inverse Rendering of Complex Scenes with Unified Color and LiDAR Reflectance Modeling
Xiaoxue Chen, Bhargav Chandaka, Chih-Hao Lin, Ya-Qin Zhang, David A. Forsyth, Hao Zhao, Shenlong Wang
摘要
We present InvRGB+L, a novel inverse rendering model that reconstructs large, relightable, and dynamic scenes from a single RGB+LiDAR sequence. Conventional inverse graphics methods rely primarily on RGB observations and use LiDAR mainly for geometric information, often resulting in suboptimal material estimates due to visible light interference. We find that LiDAR's intensity values-captured with active illumination in a different spectral range-offer complementary cues for robust material estimation under variable lighting. Inspired by this, InvRGB+L leverages LiDAR intensity cues to overcome challenges inherent in RGB-centric inverse graphics through two key innovations: (1) a novel physics-based LiDAR shading model and (2) RGB-LiDAR material consistency losses. The model produces novel-view RGB and LiDAR renderings of urban and indoor scenes and supports relighting, night simulations, and dynamic object insertions, achieving results that surpass current state-of-the-art methods in both scene-level urban inverse rendering and LiDAR simulation.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它它引用的顶会 Paper24
- Segment AnythingAlexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao 等ICCV 2023 · 被引用 13,211 次
- DUSt3R: Geometric 3D Vision Made EasyShuzhe Wang, Vincent Leroy, Yohann Cabon, Boris Chidlovskii 等CVPR 2024 · 被引用 302 次
- Neural Inverse Rendering of an Indoor Scene From a Single ImageSoumyadip Sengupta, Jinwei Gu, Kihwan Kim, Guilin Liu 等ICCV 2019 · 被引用 172 次
- Neural LiDAR Fields for Novel View SynthesisShengyu Huang, Zan Gojcic, Zian Wang, Francis Williams 等ICCV 2023 · 被引用 80 次
- EMLight: Lighting Estimation via Spherical Distribution ApproximationFangneng Zhan, Changgong Zhang, Yingchen Yu, Yuan Chang 等AAAI 2021 · 被引用 73 次
相关 Paper
- Ambient-robust Inverse Rendering using Active RGB-NIR ImagingHoon-Gyu Chung, Jinnyeong Kim, Hyunwoo Kang, Seung-Hwan BaekSIGGRAPH 2026
- IRIS: Inverse Rendering of Indoor Scenes from Low Dynamic Range ImagesChih-Hao Lin, Jia-Bin Huang, Zhengqin Li, Zhao Dong 等CVPR 2025
- Factored-NeuS: Reconstructing Surfaces, Illumination, and Materials of Possibly Glossy ObjectsYue Fan, Ningjing Fan, Ivan Skorokhodov, Oleg Voynov 等CVPR 2025
- Unsupervised Intrinsic Image Decomposition with LiDAR IntensityShogo Sato, Yasuhiro Yao, Taiga Yoshida, Takuhiro Kaneko 等CVPR 2023
- PBR-NeRF: Inverse Rendering with Physics-Based Neural FieldsSean Wu, Shamik Basu, Tim Broedermann, Luc Van Gool 等CVPR 2025
