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Recent advances in differentiable rendering have enabled high-quality reconstruction of 3D scenes from multi-view images. Most methods rely on simple rendering algorithms: pre-filtered direct lighting or learned representations of…

Graphics · Computer Science 2022-10-05 Jon Hasselgren , Nikolai Hofmann , Jacob Munkberg

Indoor scenes typically exhibit complex, spatially-varying appearance from global illumination, making inverse rendering a challenging ill-posed problem. This work presents an end-to-end, learning-based inverse rendering framework…

Computer Vision and Pattern Recognition · Computer Science 2022-11-24 Jingsen Zhu , Fujun Luan , Yuchi Huo , Zihao Lin , Zhihua Zhong , Dianbing Xi , Jiaxiang Zheng , Rui Tang , Hujun Bao , Rui Wang

Traditional inverse rendering techniques are based on textured meshes, which naturally adapts to modern graphics pipelines, but costly differentiable multi-bounce Monte Carlo (MC) ray tracing poses challenges for modeling global…

Graphics · Computer Science 2025-06-09 Jiakai Sun , Weijing Zhang , Zhanjie Zhang , Tianyi Chu , Guangyuan Li , Lei Zhao , Wei Xing

Inverse rendering methods have achieved remarkable performance in reconstructing high-fidelity 3D objects with disentangled geometries, materials, and environmental light. However, they still face huge challenges in reflective surface…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Tengjie Zhu , Zhuo Chen , Jingnan Gao , Yichao Yan , Xiaokang Yang

We present Neural Microfacet Fields, a method for recovering materials, geometry, and environment illumination from images of a scene. Our method uses a microfacet reflectance model within a volumetric setting by treating each sample along…

Computer Vision and Pattern Recognition · Computer Science 2023-10-18 Alexander Mai , Dor Verbin , Falko Kuester , Sara Fridovich-Keil

Inverse rendering seeks to estimate scene characteristics from a set of data images. The dominant approach is based on differential rendering using Monte-Carlo. Algorithms as such usually rely on a forward model and use an iterative…

Computer Vision and Pattern Recognition · Computer Science 2021-10-04 Ido Czerninski , Yoav Y. Schechner

Implicit neural representation has opened up new possibilities for inverse rendering. However, existing implicit neural inverse rendering methods struggle to handle strongly illuminated scenes with significant shadows and indirect…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Yanzhen Chen , Xinyu Gao , Yazhen Yuan , Yu Wu , Xiaowei Zhou , Xiaogang Jin

We present a physics-based inverse rendering method that learns the illumination, geometry, and materials of a scene from posed multi-view RGB images. To model the illumination of a scene, existing inverse rendering works either completely…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Youming Deng , Xueting Li , Sifei Liu , Ming-Hsuan Yang

Inverse rendering seeks to recover 3D geometry, surface material, and lighting from captured images, enabling advanced applications such as novel-view synthesis, relighting, and virtual object insertion. However, most existing techniques…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Chih-Hao Lin , Jia-Bin Huang , Zhengqin Li , Zhao Dong , Christian Richardt , Tuotuo Li , Michael Zollhöfer , Johannes Kopf , Shenlong Wang , Changil Kim

Inverse rendering methods aim to estimate geometry, materials and illumination from multi-view RGB images. In order to achieve better decomposition, recent approaches attempt to model indirect illuminations reflected from different…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Haoqian Wu , Zhipeng Hu , Lincheng Li , Yongqiang Zhang , Changjie Fan , Xin Yu

Modern computer vision algorithms have brought significant advancement to 3D geometry reconstruction. However, illumination and material reconstruction remain less studied, with current approaches assuming very simplified models for…

Computer Vision and Pattern Recognition · Computer Science 2019-03-19 Dejan Azinović , Tzu-Mao Li , Anton Kaplanyan , Matthias Nießner

Recent advances in implicit neural representations and differentiable rendering make it possible to simultaneously recover the geometry and materials of an object from multi-view RGB images captured under unknown static illumination.…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Yuanqing Zhang , Jiaming Sun , Xingyi He , Huan Fu , Rongfei Jia , Xiaowei Zhou

Inverse rendering aims to reconstruct geometry and reflectance of objects from images. Despite recent progress, existing methods often produces inaccurate reconstructions that are sensitive to ambient illumination conditions. Here we…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Hoon-Gyu Chung , Jinnyeong Kim , Hyunwoo Kang , Seung-Hwan Baek

Inverse rendering, the process of inferring scene properties from images, is a challenging inverse problem. The task is ill-posed, as many different scene configurations can give rise to the same image. Most existing solutions incorporate…

Computer Vision and Pattern Recognition · Computer Science 2023-10-03 Linjie Lyu , Ayush Tewari , Marc Habermann , Shunsuke Saito , Michael Zollhöfer , Thomas Leimkühler , Christian Theobalt

We propose a neural inverse rendering approach that jointly reconstructs geometry, spatially varying reflectance, and lighting conditions from multi-view images captured under varying directional lighting. Unlike prior multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Xu Cao , Takafumi Taketomi

In inverse rendering, accurately modeling visibility and indirect radiance for incident light is essential for capturing secondary effects. Due to the absence of a powerful Gaussian ray tracer, previous 3DGS-based methods have either…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Chun Gu , Xiaofei Wei , Zixuan Zeng , Yuxuan Yao , Li Zhang

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xiangyang Zhu , Yiling Pan , Bailin Deng , Bin Wang

Recent advances in Gaussian Splatting-based inverse rendering extend Gaussian primitives with shading parameters and physically grounded light transport, enabling high-quality material recovery from dense multi-view captures. However, these…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Patrick Noras , Jun Myeong Choi , Didier Stricker , Pieter Peers , Roni Sengupta

Multi-view inverse rendering aims to recover geometry, materials, and illumination consistently across multiple viewpoints. When applied to multi-view images, existing single-view approaches often ignore cross-view relationships, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Xiangzuo Wu , Chengwei Ren , Jun Zhou , Xiu Li , Yuan Liu

Existing time-resolved non-line-of-sight (NLOS) imaging methods reconstruct hidden scenes by inverting the optical paths of indirect illumination measured at visible relay surfaces. These methods are prone to reconstruction artifacts due to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Kiseok Choi , Inchul Kim , Dongyoung Choi , Julio Marco , Diego Gutierrez , Min H. Kim
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