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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

Neural radiance fields have achieved remarkable performance in modeling the appearance of 3D scenes. However, existing approaches still struggle with the view-dependent appearance of glossy surfaces, especially under complex lighting of…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Li Ma , Vasu Agrawal , Haithem Turki , Changil Kim , Chen Gao , Pedro Sander , Michael Zollhöfer , Christian Richardt

3D Gaussian Splatting is emerging as a state-of-the-art technique in novel view synthesis, recognized for its impressive balance between visual quality, speed, and rendering efficiency. However, reliance on third-degree spherical harmonics…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Yiwen Wang , Siyuan Chen , Ran Yi

Recently, 3D Gaussian Splatting (3DGS) has revolutionized radiance field reconstruction, manifesting efficient and high-fidelity novel view synthesis. However, accurately representing surfaces, especially in large and complex scenarios,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Yang Liu , Chuanchen Luo , Zhongkai Mao , Junran Peng , Zhaoxiang Zhang

High dynamic range novel view synthesis (HDR-NVS) reconstructs scenes with dynamic details by fusing multi-exposure low dynamic range (LDR) views, yet it struggles to capture ambient illumination-dependent appearance. Implicitly supervising…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Huimin Zeng , Yue Bai , Hailing Wang , Yun Fu

Recent advances in neural rendering have shown great potential for reconstructing scenes from multiview images. However, accurately representing objects with glossy surfaces remains a challenge for existing methods. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Ruofan Liang , Huiting Chen , Chunlin Li , Fan Chen , Selvakumar Panneer , Nandita Vijaykumar

Neural implicit representations, including Neural Distance Fields and Neural Radiance Fields, have demonstrated significant capabilities for reconstructing surfaces with complicated geometry and topology, and generating novel views of a…

Graphics · Computer Science 2024-02-08 Lin Gao , Jie Yang , Bo-Tao Zhang , Jia-Mu Sun , Yu-Jie Yuan , Hongbo Fu , Yu-Kun Lai

Recently, 3D Gaussian Splatting (3DGS), an explicit scene representation technique, has shown significant promise for dynamic novel-view synthesis from monocular video input. However, purely data-driven 3DGS often struggles to capture the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Haoqin Hong , Ding Fan , Fubin Dou , Zhi-Li Zhou , Haoran Sun , Congcong Zhu , Jingrun Chen

Accurately modeling light transport is essential for realistic image synthesis. Photon mapping provides physically grounded estimates of complex global illumination effects such as caustics and specular-diffuse interactions, yet its…

We present InvRGB+L, a novel inverse rendering model that reconstructs large, relightable, and dynamic scenes from a single RGB+LiDAR sequence. Conventional inverse graphics methods rely primarily on RGB observations and use LiDAR mainly…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Xiaoxue Chen , Bhargav Chandaka , Chih-Hao Lin , Ya-Qin Zhang , David Forsyth , Hao Zhao , Shenlong Wang

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

The boundary representation (B-Rep) models a 3D solid as its explicit boundaries: trimmed corners, edges, and faces. Recovering B-Rep representation from unstructured data is a challenging and valuable task of computer vision and graphics.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Jiaxing Yu , Dongyang Ren , Hangyu Xu , Zhouyuxiao Yang , Yuanqi Li , Jie Guo , Zhengkang Zhou , Yanwen Guo

Gaussian Splatting have demonstrated remarkable novel view synthesis performance at high rendering frame rates. Optimization-based inverse rendering within complex capture scenarios remains however a challenging problem. A particular case…

Graphics · Computer Science 2025-12-08 Mae Younes , Adnane Boukhayma

We present FPGS, a feed-forward photorealistic style transfer method of large-scale radiance fields represented by Gaussian Splatting. FPGS, stylizes large-scale 3D scenes with arbitrary, multiple style reference images without additional…

Graphics · Computer Science 2025-03-14 GeonU Kim , Kim Youwang , Lee Hyoseok , Tae-Hyun Oh

Feed-forward 3D Gaussian Splatting methods have achieved impressive reconstruction quality for autonomous driving scenes, yet they entangle scene geometry with transient appearance properties such as lighting, weather, and time of day. This…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Quentin Herau , Tianshuo Xu , Depu Meng , Jiezhi Yang , Chensheng Peng , Spencer Sherk , Yihan Hu , Wei Zhan

3D Gaussian Splatting (3DGS) has shown promising performance in novel view synthesis. Previous methods adapt it to obtaining surfaces of either individual 3D objects or within limited scenes. In this paper, we make the first attempt to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Junyi Chen , Weicai Ye , Yifan Wang , Danpeng Chen , Di Huang , Wanli Ouyang , Guofeng Zhang , Yu Qiao , Tong He

3D Gaussian Splatting (3DGS) has recently emerged as a state-of-the-art 3D reconstruction and rendering technique due to its high-quality results and fast training and rendering time. However, pixels covered by the same Gaussian are always…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Brian Chao , Hung-Yu Tseng , Lorenzo Porzi , Chen Gao , Tuotuo Li , Qinbo Li , Ayush Saraf , Jia-Bin Huang , Johannes Kopf , Gordon Wetzstein , Changil Kim

Novel view synthesis for underwater scene reconstruction presents unique challenges due to complex light-media interactions. Optical scattering and absorption in water body bring inhomogeneous medium attenuation interference that disrupts…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Jieyu Yuan , Yujun Li , Yuanlin Zhang , Chunle Guo , Xiongxin Tang , Ruixing Wang , Chongyi Li

Reconstructing complete and interactive 3D scenes remains a fundamental challenge in computer vision and robotics, particularly due to persistent object occlusions and limited sensor coverage. Multiview observations from a single scene scan…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Wenhao Hu , Zesheng Li , Haonan Zhou , Liu Liu , Xuexiang Wen , Zhizhong Su , Xi Li , Gaoang Wang

It is vital to infer a signed distance function (SDF) in multi-view based surface reconstruction. 3D Gaussian splatting (3DGS) provides a novel perspective for volume rendering, and shows advantages in rendering efficiency and quality.…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Wenyuan Zhang , Yu-Shen Liu , Zhizhong Han
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