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Inverse rendering is the problem of decomposing an image into its intrinsic components, i.e. albedo, normal and lighting. To solve this ill-posed problem from single image, state-of-the-art methods in shape from shading mostly resort to…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Mona Zehni , Shaona Ghosh , Krishna Sridhar , Sethu Raman

We present the first system for physically based, neural inverse rendering from multi-viewpoint videos of propagating light. Our approach relies on a time-resolved extension of neural radiance caching -- a technique that accelerates inverse…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Anagh Malik , Benjamin Attal , Andrew Xie , Matthew O'Toole , David B. Lindell

Decoupling lighting from geometry using unconstrained photo collections is notoriously challenging. Solving it would benefit many users as creating complex 3D assets takes days of manual labor. Many previous works have attempted to address…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Joanna Kaleta , Kacper Kania , Tomasz Trzcinski , Marek Kowalski

This paper presents a 3D Gaussian Inverse Rendering (GIR) method, employing 3D Gaussian representations to effectively factorize the scene into material properties, light, and geometry. The key contributions lie in three-fold. We compute…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Yahao Shi , Yanmin Wu , Chenming Wu , Xing Liu , Chen Zhao , Haocheng Feng , Jian Zhang , Bin Zhou , Errui Ding , Jingdong Wang

Being able to see beyond the direct line of sight is an intriguing prospective and could benefit a wide variety of important applications. Recent work has demonstrated that time-resolved measurements of indirect diffuse light contain…

Graphics · Computer Science 2019-10-24 Julian Iseringhausen , Matthias B. Hullin

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

Radiance field methods represent the state of the art in reconstructing complex scenes from multi-view photos. However, these reconstructions often suffer from one or both of the following limitations: First, they typically represent scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Chao Wang , Krzysztof Wolski , Bernhard Kerbl , Ana Serrano , Mojtaba Bemana , Hans-Peter Seidel , Karol Myszkowski , Thomas Leimkühler

2D images are observations of the 3D physical world depicted with the geometry, material, and illumination components. Recovering these underlying intrinsic components from 2D images, also known as inverse rendering, usually requires a…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Xingang Pan , Ayush Tewari , Lingjie Liu , Christian Theobalt

Existing methods for relightable view synthesis -- using a set of images of an object under unknown lighting to recover a 3D representation that can be rendered from novel viewpoints under a target illumination -- are based on inverse…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Xiaoming Zhao , Pratul P. Srinivasan , Dor Verbin , Keunhong Park , Ricardo Martin Brualla , Philipp Henzler

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

3D Gaussian Splatting (3DGS) is a process that enables the direct creation of 3D objects from 2D images. This representation offers numerous advantages, including rapid training and rendering. However, a significant limitation of 3DGS is…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Krzysztof Byrski , Marcin Mazur , Jacek Tabor , Tadeusz Dziarmaga , Marcin Kądziołka , Dawid Baran , Przemysław Spurek

The goal of inverse rendering is to decompose geometry, lights, and materials given pose multi-view images. To achieve this goal, we propose neural direct and joint inverse rendering, NDJIR. Different from prior works which relies on some…

Computer Vision and Pattern Recognition · Computer Science 2023-02-03 Kazuki Yoshiyama , Takuya Narihira

We address the challenge of relighting a single image or video, a task that demands precise scene intrinsic understanding and high-quality light transport synthesis. Existing end-to-end relighting models are often limited by the scarcity of…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Kai He , Ruofan Liang , Jacob Munkberg , Jon Hasselgren , Nandita Vijaykumar , Alexander Keller , Sanja Fidler , Igor Gilitschenski , Zan Gojcic , Zian Wang

One of the key advantages of 3D rendering is its ability to simulate intricate scenes accurately. One of the most widely used methods for this purpose is Gaussian Splatting, a novel approach that is known for its rapid training and…

Graphics · Computer Science 2024-05-31 Artur Kasymov , Bartosz Czekaj , Marcin Mazur , Jacek Tabor , Przemysław Spurek

We propose two novel ideas (adoption of deferred rendering and mesh-based representation) to improve the quality of 3D Gaussian splatting (3DGS) based inverse rendering. We first report a problem incurred by hidden Gaussians, where…

Graphics · Computer Science 2024-09-17 Euntae Choi , Sungjoo Yoo

Modeling outdoor scenes for the synthetic 3D environment requires the recovery of reflectance/albedo information from raw images, which is an ill-posed problem due to the complicated unmodeled physics in this process (e.g., indirect…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Shuang Song , Rongjun Qin

This paper aims to recover object materials from posed images captured under an unknown static lighting condition. Recent methods solve this task by optimizing material parameters through differentiable physically based rendering. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Xi Chen , Sida Peng , Dongchen Yang , Yuan Liu , Bowen Pan , Chengfei Lv , Xiaowei Zhou

State-of-the-art techniques for 3D reconstruction are largely based on volumetric scene representations, which require sampling multiple points to compute the color arriving along a ray. Using these representations for more general inverse…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Benjamin Attal , Dor Verbin , Ben Mildenhall , Peter Hedman , Jonathan T. Barron , Matthew O'Toole , Pratul P. Srinivasan

In this work, we address specular appearance in inverse rendering using 2D Gaussian splatting with deferred shading and argue for a refinement stage to improve specular detail, thereby bridging the gap with reconstruction-only methods. Our…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Georgios Kouros , Minye Wu , Tinne Tuytelaars

We present a spatial and angular Gaussian based representation and a triple splatting process, for real-time, high-quality novel lighting-and-view synthesis from multi-view point-lit input images. To describe complex appearance, we employ a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Zoubin Bi , Yixin Zeng , Chong Zeng , Fan Pei , Xiang Feng , Kun Zhou , Hongzhi Wu