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We introduce SeaSplat, a method to enable real-time rendering of underwater scenes leveraging recent advances in 3D radiance fields. Underwater scenes are challenging visual environments, as rendering through a medium such as water…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Daniel Yang , John J. Leonard , Yogesh Girdhar

Can we capture shape and reflectance in stealth? Such capability would be valuable for many application domains in vision, xR, robotics, and HCI. We introduce structured polarization for invisible depth and reflectance sensing (SPIDeRS),…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Tomoki Ichikawa , Shohei Nobuhara , Ko Nishino

Reconstructing a 3D scene from images is challenging due to the different ways light interacts with surfaces depending on the viewer's position and the surface's material. In classical computer graphics, materials can be classified as…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Mateusz Nowak , Wojciech Jarosz , Peter Chin

3D Gaussian Splatting (3DGS) enables real-time view synthesis in colonoscopy but assumes static illumination, making it incompatible with the strong photometric variations caused by the moving light source and camera. This mismatch leads…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Hao Wang , Ying Zhou , Haoyu Zhao , Rui Wang , Qiang Hu , Xing Zhang , Qiang Li , Zhiwei Wang

Generating ground-level views and coherent 3D site models from aerial-only imagery is challenging due to extreme viewpoint changes, missing intermediate observations, and large scale variations. Existing methods either refine renderings…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Sirshapan Mitra , Yogesh S. Rawat

3D Gaussian Splatting (3DGS) enables efficient training and fast novel view synthesis in static environments. To address challenges posed by transient objects, distractor-free 3DGS methods have emerged and shown promising results when dense…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yi Gu , Zhaorui Wang , Jiahang Cao , Jiaxu Wang , Mingle Zhao , Dongjun Ye , Renjing Xu

3D Gaussian Splatting (3DGS) has emerged as a novel paradigm for 3D reconstruction from satellite imagery. However, in multi-temporal satellite images, prevalent shadows exhibit significant inconsistencies due to varying illumination…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Feng Luo , Hongbo Pan , Xiang Yang , Baoyu Jiang , Fengqing Liu , Tao Huang

Geometry reconstruction of textureless, non-Lambertian objects under unknown natural illumination (i.e., in the wild) remains challenging as correspondences cannot be established and the reflectance cannot be expressed in simple analytical…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Kohei Yamashita , Shohei Nobuhara , Ko Nishino

Ray-tracing-based 3D Gaussian splatting (3DGS) methods overcome the limitations of rasterization -- rigid pinhole camera assumptions, inaccurate shadows, and lack of native reflection or refraction -- but remain slower due to the cost of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Peiyu Xu , Xin Sun , Krishna Mullia , Raymond Fei , Iliyan Georgiev , Shuang Zhao

3D Gaussian Splatting has advanced radiance field reconstruction, enabling high-quality view synthesis and fast rendering in 3D modeling. While adversarial attacks on object detection models are well-studied for 2D images, their impact on…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Abdurrahman Zeybey , Mehmet Ergezer , Tommy Nguyen

Recent advancements in 3D Gaussian Splatting(3DGS) have significantly improved semantic scene understanding, enabling natural language queries to localize objects within a scene. However, existing methods primarily focus on embedding…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Xihan Wang , Dianyi Yang , Yu Gao , Yufeng Yue , Yi Yang , Mengyin Fu

3D Gaussian Splatting (3DGS) has emerged as a key rendering pipeline for digital asset creation due to its balance between efficiency and visual quality. To address the issues of unstable pose estimation and scene representation distortion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Meijun Guo , Yongliang Shi , Caiyun Liu , Yixiao Feng , Ming Ma , Tinghai Yan , Weining Lu , Bin Liang

Glossy objects present a significant challenge for 3D reconstruction from multi-view input images under natural lighting. In this paper, we introduce PBIR-NIE, an inverse rendering framework designed to holistically capture the geometry,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Guangyan Cai , Fujun Luan , Miloš Hašan , Kai Zhang , Sai Bi , Zexiang Xu , Iliyan Georgiev , Shuang Zhao

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

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

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

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

Differentiable rendering techniques have recently shown promising results for free-viewpoint video synthesis of characters. However, such methods, either Gaussian Splatting or neural implicit rendering, typically necessitate per-subject…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Boyao Zhou , Shunyuan Zheng , Hanzhang Tu , Ruizhi Shao , Boning Liu , Shengping Zhang , Liqiang Nie , Yebin Liu

Recent advancements in 3D Gaussian Splatting (3D-GS) have revolutionized novel view synthesis, facilitating real-time, high-quality image rendering. However, in scenarios involving reflective surfaces, particularly mirrors, 3D-GS often…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Zihan Wang , Shuzhe Wang , Matias Turkulainen , Junyuan Fang , Juho Kannala

Recent advances in Gaussian Splatting have enabled fast, high-fidelity 3D scene generation, yet these methods remain purely visual and lack an understanding of how shapes behave in the physical world. We introduce Physics-Guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Zachary Lee , Maxwell Jacobson , Yexiang Xue