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Reconstruction and intrinsic decomposition of scenes from captured imagery would enable many applications such as relighting and virtual object insertion. Recent NeRF based methods achieve impressive fidelity of 3D reconstruction, but bake…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Zian Wang , Tianchang Shen , Jun Gao , Shengyu Huang , Jacob Munkberg , Jon Hasselgren , Zan Gojcic , Wenzheng Chen , Sanja Fidler

3D Gaussian Splatting (3DGS) has established itself as a leading technique for 3D reconstruction and novel view synthesis of static scenes, achieving outstanding rendering quality and fast training. However, the method does not explicitly…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Margherita Lea Corona , Wieland Morgenstern , Peter Eisert , Anna Hilsmann

Inverse rendering aims at recovering both geometry and materials of objects. It provides a more compatible reconstruction for conventional rendering engines, compared with the neural radiance fields (NeRFs). On the other hand, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Haoyuan Wang , Wenbo Hu , Lei Zhu , Rynson W. H. Lau

Inverse rendering pipelines are gaining prominence in realizing photo-realistic reconstruction of real-world objects for emulating them in virtual reality scenes. Apart from material reflectances, spectral rendering and in-scene…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Parisha Joshi , Daljit Singh J. Dhillon

We demonstrate the feasibility of integrating physics-based animations of solids and fluids with 3D Gaussian Splatting (3DGS) to create novel effects in virtual scenes reconstructed using 3DGS. Leveraging the coherence of the Gaussian…

Radiance fields have gained tremendous success with applications ranging from novel view synthesis to geometry reconstruction, especially with the advent of Gaussian splatting. However, they sacrifice modeling of material reflective…

Graphics · Computer Science 2025-09-30 Kaiwen Jiang , Jia-Mu Sun , Zilu Li , Dan Wang , Tzu-Mao Li , Ravi Ramamoorthi

We present a method to edit complex indoor lighting from a single image with its predicted depth and light source segmentation masks. This is an extremely challenging problem that requires modeling complex light transport, and disentangling…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Zhengqin Li , Jia Shi , Sai Bi , Rui Zhu , Kalyan Sunkavalli , Miloš Hašan , Zexiang Xu , Ravi Ramamoorthi , Manmohan Chandraker

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

Recent 3D Gaussian Splatting (3DGS) methods have demonstrated the feasibility of self-driving scene reconstruction and novel view synthesis. However, most existing methods either rely solely on cameras or use LiDAR only for Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 ZY Chen , F Zhu , H Zhu , DY Kong , XK Kuang , YJ Zhang , CM Jiang

Recently, 3D Gaussian Splatting (3D-GS) has achieved significant success in real-time, high-quality 3D scene rendering. However, it faces several challenges, including Gaussian redundancy, limited ability to capture view-dependent effects,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Junxi Jin , Xiulai Li , Haiping Huang , Lianjun Liu , Yujie Sun , Logan Liu

We present SSD-GS, a physically-based relighting framework built upon 3D Gaussian Splatting (3DGS) that achieves high-quality reconstruction and photorealistic relighting under novel lighting conditions. In physically-based relighting,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Iris Zheng , Guojun Tang , Alexander Doronin , Paul Teal , Fang-Lue Zhang

3D reconstruction and relighting of objects made from scattering materials present a significant challenge due to the complex light transport beneath the surface. 3D Gaussian Splatting introduced high-quality novel view synthesis at…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Jan-Niklas Dihlmann , Arjun Majumdar , Andreas Engelhardt , Raphael Braun , Hendrik P. A. Lensch

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

Novel view synthesis has experienced significant advancements owing to increasingly capable NeRF- and 3DGS-based methods. However, reflective object reconstruction remains challenging, lacking a proper solution to achieve real-time,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Yuxuan Yao , Zixuan Zeng , Chun Gu , Xiatian Zhu , Li Zhang

This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the scalability issue, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hanyue Zhang , Zhiliu Yang , Xinhe Zuo , Yuxin Tong , Ying Long , Chen Liu

We present 3D Surface Splatting (3DSS), the first differentiable surface splatting renderer for physically-based inverse rendering from multi-view images. Our central insight is that the surface separation problem at the heart of surface…

Graphics · Computer Science 2026-05-14 Mae Younes , Adnane Boukhayma

The use of 3D Gaussians as representation of radiance fields has enabled high quality novel view synthesis at real-time rendering speed. However, the choice of optimising the outgoing radiance of each Gaussian independently as spherical…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Zhe Jun Tang , Tat-Jen Cham

The correct insertion of virtual objects in images of real-world scenes requires a deep understanding of the scene's lighting, geometry and materials, as well as the image formation process. While recent large-scale diffusion models have…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Ruofan Liang , Zan Gojcic , Merlin Nimier-David , David Acuna , Nandita Vijaykumar , Sanja Fidler , Zian Wang

We propose a 3D Gaussian splatting-based framework for outdoor relighting that leverages intrinsic image decomposition to precisely integrate sunlight, sky radiance, and indirect lighting from unconstrained photo collections. Unlike prior…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Haiyang Bai , Jiaqi Zhu , Songru Jiang , Wei Huang , Tao Lu , Yuanqi Li , Jie Guo , Runze Fu , Yanwen Guo , Lijun Chen

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
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