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We consider the challenging problem of outdoor lighting estimation for the goal of photorealistic virtual object insertion into photographs. Existing works on outdoor lighting estimation typically simplify the scene lighting into an…

Computer Vision and Pattern Recognition · Computer Science 2022-08-22 Zian Wang , Wenzheng Chen , David Acuna , Jan Kautz , Sanja Fidler

This paper addresses the task of estimating the light arriving from all directions to a 3D point observed at a selected pixel in an RGB image. This task is challenging because it requires predicting a mapping from a partial scene…

Computer Vision and Pattern Recognition · Computer Science 2019-06-19 Shuran Song , Thomas Funkhouser

We propose an automatic method to infer high dynamic range illumination from a single, limited field-of-view, low dynamic range photograph of an indoor scene. In contrast to previous work that relies on specialized image capture, user…

Computer Vision and Pattern Recognition · Computer Science 2017-11-22 Marc-André Gardner , Kalyan Sunkavalli , Ersin Yumer , Xiaohui Shen , Emiliano Gambaretto , Christian Gagné , Jean-François Lalonde

We present a efficient multi-view inverse rendering method for large-scale real-world indoor scenes that reconstructs global illumination and physically-reasonable SVBRDFs. Unlike previous representations, where the global illumination of…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Zhen Li , Lingli Wang , Mofang Cheng , Cihui Pan , Jiaqi Yang

We present SGS-Intrinsic, an indoor inverse rendering framework that works well for sparse-view images. Unlike existing 3D Gaussian Splatting (3DGS) based methods that focus on object-centric reconstruction and fail to work under sparse…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Jiahao Niu , Rongjia Zheng , Wenju Xu , Wei-Shi Zheng , Qing Zhang

Virtual production (VP) use LED walls to provide both background imagery and image-based lighting. While this enables on-set compositing, it couples lighting to background and scene appearance, limiting flexibility for downstream editing.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Adrian Azzarelli , Nantheera Anantrasirichai , James Pollock , David R. Bull

In this paper, we propose the first framework that leverages physically-based inverse rendering for novel lighting generation on existing real-world human demonstrations of robotic manipulation tasks. Specifically, inverse rendering…

Robotics · Computer Science 2025-09-19 Shutong Jin , Lezhong Wang , Ben Temming , Florian T. Pokorny

Real-time rendering with global illumination is crucial to afford the user realistic experience in virtual environments. We present a learning-based estimator to predict diffuse indirect illumination in screen space, which then is combined…

Graphics · Computer Science 2025-11-06 Meng Gai , Guoping Wang , Sheng Li

3D Gaussian Splatting shows great potential in reconstructing photo-realistic 3D scenes. However, these methods typically bake illumination into their representations, limiting their use for physically-based rendering and scene editing.…

Graphics · Computer Science 2025-04-03 Zirui Wu , Jianteng Chen , Laijian Li , Shaoteng Wu , Zhikai Zhu , Kang Xu , Martin R. Oswald , Jie Song

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…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jiaye Wu , Saeed Hadadan , Geng Lin , Peihan Tu , Matthias Zwicker , David Jacobs , Roni Sengupta

We propose a novel inverse rendering method that enables the transformation of existing indoor panoramas with new indoor furniture layouts under natural illumination. To achieve this, we captured indoor HDR panoramas along with real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Guanzhou Ji , Azadeh O. Sawyer , Srinivasa G. Narasimhan

We present PhySG, an end-to-end inverse rendering pipeline that includes a fully differentiable renderer and can reconstruct geometry, materials, and illumination from scratch from a set of RGB input images. Our framework represents…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Kai Zhang , Fujun Luan , Qianqian Wang , Kavita Bala , Noah Snavely

This paper presents an illumination estimation method for virtual objects in real environment by learning. While previous works tackled this problem by reconstructing high dynamic range (HDR) environment maps or the corresponding spherical…

Computer Vision and Pattern Recognition · Computer Science 2020-07-14 Di Xu , Zhen Li , Yanning Zhang , Qi Cao

We consider the challenging problem of predicting intrinsic object properties from a single image by exploiting differentiable renderers. Many previous learning-based approaches for inverse graphics adopt rasterization-based renderers and…

Computer Vision and Pattern Recognition · Computer Science 2021-11-02 Wenzheng Chen , Joey Litalien , Jun Gao , Zian Wang , Clement Fuji Tsang , Sameh Khamis , Or Litany , Sanja Fidler

We propose GS-IR, a novel inverse rendering approach based on 3D Gaussian Splatting (GS) that leverages forward mapping volume rendering to achieve photorealistic novel view synthesis and relighting results. Unlike previous works that use…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Zhihao Liang , Qi Zhang , Ying Feng , Ying Shan , Kui Jia

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

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

Image relighting is the task of showing what a scene from a source image would look like if illuminated differently. Inverse graphics schemes recover an explicit representation of geometry and a set of chosen intrinsics, then relight with…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xiao Zhang , William Gao , Seemandhar Jain , Michael Maire , David A. Forsyth , Anand Bhattad

3D Gaussian Splatting (3DGS) has demonstrated impressive capabilities in novel view synthesis. However, rendering reflective objects remains a significant challenge, particularly in inverse rendering and relighting. We introduce RTR-GS, a…

Graphics · Computer Science 2025-12-17 Yongyang Zhou , Fang-Lue Zhang , Zichen Wang , Lei Zhang

Inverse rendering seeks to reconstruct both geometry and spatially varying BRDFs (SVBRDFs) from captured images. To address the inherent ill-posedness of inverse rendering, basis BRDF representations are commonly used, modeling SVBRDFs as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Hoon-Gyu Chung , Seokjun Choi , Seung-Hwan Baek