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Dynamic scene reconstruction represents a fundamental yet demanding challenge in computer vision and robotics. While recent progress in 3DGS-based methods has advanced dynamic scene modeling, obtaining high-fidelity rendering and accurate…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Yinan Deng , Jianyu Dou , Jiahui Wang , Jingyu Zhao , Yi Yang , Yufeng Yue

We present SpectroMotion, a novel approach that combines 3D Gaussian Splatting (3DGS) with physically-based rendering (PBR) and deformation fields to reconstruct dynamic specular scenes. Previous methods extending 3DGS to model dynamic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Cheng-De Fan , Chen-Wei Chang , Yi-Ruei Liu , Jie-Ying Lee , Jiun-Long Huang , Yu-Chee Tseng , Yu-Lun Liu

Inverse rendering aims to decompose a scene into its geometry, material properties and light conditions under a certain rendering model. It has wide applications like view synthesis, relighting, and scene editing. In recent years, inverse…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Geng Lin , Matthias Zwicker

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) representations have demonstrated remarkable performance in novel view synthesis; further, material-lighting disentanglement on 3DGS warrants relighting capabilities and its adaptability to broader…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Kai Ye , Chong Gao , Guanbin Li , Wenzheng Chen , Baoquan Chen

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

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

Decomposing geometry, materials and lighting from a set of images, namely inverse rendering, has been a long-standing problem in computer vision and graphics. Recent advances in neural rendering enable photo-realistic and plausible inverse…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Silong Yong , Venkata Nagarjun Pudureddiyur Manivannan , Bernhard Kerbl , Zifu Wan , Simon Stepputtis , Katia Sycara , Yaqi Xie

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

Reconstructing intricate, ever-changing environments remains a central ambition in computer vision, yet existing solutions often crumble before the complexity of real-world dynamics. We present DynaSplat, an approach that extends Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Junli Deng , Ping Shi , Qipei Li , Jinyang Guo

We present GI-GS, a novel inverse rendering framework that leverages 3D Gaussian Splatting (3DGS) and deferred shading to achieve photo-realistic novel view synthesis and relighting. In inverse rendering, accurately modeling the shading…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Hongze Chen , Zehong Lin , Jun Zhang

Dynamic scene reconstruction is a long-term challenge in the field of 3D vision. Recently, the emergence of 3D Gaussian Splatting has provided new insights into this problem. Although subsequent efforts rapidly extend static 3D Gaussian to…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Ruijie Zhu , Yanzhe Liang , Hanzhi Chang , Jiacheng Deng , Jiahao Lu , Wenfei Yang , Tianzhu Zhang , Yongdong Zhang

Previous surface reconstruction methods either suffer from low geometric accuracy or lengthy training times when dealing with real-world complex dynamic scenes involving multi-person activities, and human-object interactions. To tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shuo Wang , Binbin Huang , Ruoyu Wang , Shenghua Gao

Recovering the intrinsic physical attributes of a scene from images, generally termed as the inverse rendering problem, has been a central and challenging task in computer vision and computer graphics. In this paper, we present GUS-IR, a…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zhihao Liang , Hongdong Li , Kui Jia , Kailing Guo , Qi Zhang

The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Traditional methods relying on dense point clouds and triangular meshes struggle with moving…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peizhen Zheng , Dongjing Jiang , Qingchong Jiao , Redouane EL Bouchtaoui , Flynnwell Jianfei Zhang

High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with handheld cameras. We present a method that adapts to camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Otto Seiskari , Jerry Ylilammi , Valtteri Kaatrasalo , Pekka Rantalankila , Matias Turkulainen , Juho Kannala , Esa Rahtu , Arno Solin

Reconstructing dynamic 3D scenes from monocular video remains fundamentally challenging due to the need to jointly infer motion, structure, and appearance from limited observations. Existing dynamic scene reconstruction methods based on…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Jiahui Li , Shengeng Tang , Jingxuan He , Gang Huang , Zhangye Wang , Yantao Pan , Lechao Cheng

Gaussian Splatting (GS) has emerged as an effective representation for photorealistic rendering, but the underlying geometry, material, and lighting remain entangled, hindering scene editing. Existing GS-based methods struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Kang Du , Zhihao Liang , Yulin Shen , Zeyu Wang

Accurate geometric surface reconstruction, providing essential environmental information for navigation and manipulation tasks, is critical for enabling robotic self-exploration and interaction. Recently, 3D Gaussian Splatting (3DGS) has…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Tengfei Wang , Xin Wang , Yongmao Hou , Zhaoning Zhang , Yiwei Xu , Zongqian Zhan

3D Gaussian Splatting (GS) enables highly photorealistic scene reconstruction from posed image sequences but struggles with viewpoint extrapolation due to its anisotropic nature, leading to overfitting and poor generalization, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shuohan Tao , Boyao Zhou , Hanzhang Tu , Yuwang Wang , Yebin Liu
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