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3D Gaussian Splatting (3DGS) is a leading 3D scene reconstruction method, obtaining high-quality reconstruction with real-time rendering runtime performance. The main idea behind 3DGS is to represent the scene as a collection of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rajaei Khatib , Raja Giryes

3D Gaussian Splatting (3DGS) has recently advanced radiance field reconstruction by offering superior capabilities for novel view synthesis and real-time rendering speed. However, its strategy of blending optimization and adaptive density…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Rong Liu , Rui Xu , Yue Hu , Meida Chen , Andrew Feng

3D Gaussian splatting has achieved very impressive performance in real-time novel view synthesis. However, it often suffers from over-reconstruction during Gaussian densification where high-variance image regions are covered by a few large…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Jiahui Zhang , Fangneng Zhan , Muyu Xu , Shijian Lu , Eric Xing

We introduce a probabilistic splat-based radiance field framework that retains the fast rasterization and test-time efficiency of 3D Gaussian Splatting (3DGS) while replacing heuristic primitive manipulation with gradient-based optimization…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Mia Gaia Polansky , George Kopanas , Stephan Garbin , Todd Zickler , Dor Verbin

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

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

Although 3D Gaussian Splatting (3DGS) has demonstrated promising results in novel view synthesis, its performance degrades dramatically with sparse inputs and generates undesirable artifacts. As the number of training views decreases, the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Yexing Xu , Longguang Wang , Minglin Chen , Sheng Ao , Li Li , Yulan Guo

3D Gaussian Splatting (3DGS) has emerged as a powerful approach for novel view synthesis. However, the number of Gaussian primitives often grows substantially during training as finer scene details are reconstructed, leading to increased…

Image and Video Processing · Electrical Eng. & Systems 2026-05-13 Hung Nguyen , An Le , Truong Nguyen

In-the-wild 3D Gaussian Splatting remains challenging due to transient distractors and illumination-induced cross-view appearance inconsistencies. Existing methods mainly rely on image-level masking to suppress unreliable supervision, but…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Yulei Kang , Tianze Zhu , Jian-Fang Hu , Jianhuang Lai , Wei-Shi Zheng

3D Gaussian Splatting (3DGS) has garnered significant attention due to its superior scene representation fidelity and real-time rendering performance, especially for dynamic 3D scene reconstruction (\textit{i.e.}, 4D reconstruction).…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Henan Wang , Hanxin Zhu , Xinliang Gong , Tianyu He , Xin Li , Zhibo Chen

Dynamic novel view synthesis (NVS) is essential for creating immersive experiences. Existing approaches have advanced dynamic NVS by introducing 3D Gaussian Splatting (3DGS) with implicit deformation fields or indiscriminately assigned…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Kaizhe Zhang , Yijie Zhou , Weizhan Zhang , Caixia Yan , Haipeng Du , yugui xie , Yu-Hui Wen , Yong-Jin Liu

Recent progress in feed-forward 3D Gaussian Splatting (3DGS) has notably improved rendering quality. However, the spatially uniform and highly redundant 3DGS map generated by previous feed-forward 3DGS methods limits their integration into…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Zicheng Zhang , Xiangting Meng , Ke Wu , Wenchao Ding

Reconstructing high-quality 3D models from sparse 2D images has garnered significant attention in computer vision. Recently, 3D Gaussian Splatting (3DGS) has gained prominence due to its explicit representation with efficient training speed…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Keng-Wei Chang , Zi-Ming Wang , Shang-Hong Lai

Feedforward 3D Gaussian Splatting (3DGS) often struggles in trajectory-based sparse-view driving scenes. Existing Gaussian repair methods mainly target optimization-based 3DGS, while diffusion-based repair is typically restricted to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Rui Song , Tianhui Cai , Markus Gross , Xingcheng Zhou , Zewei Zhou , Zhiyu Huang , Olaf Wysocki , Jiaqi Ma

Standard Gaussian splatting methods rely on heuristic densification and pruning to adaptively allocate primitives during training, and the resulting Gaussian count strongly influences both reconstruction quality and runtime. This makes…

Graphics · Computer Science 2026-05-18 Pratik Singh Bisht , Andreas Kolb

Compression techniques for 3D Gaussian Splatting (3DGS) have recently achieved considerable success in minimizing storage overhead for 3D Gaussians while preserving high rendering quality. Despite the impressive storage reduction, the lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Seungjoo Shin , Jaesik Park , Sunghyun Cho

Efficiently synthesizing novel views from sparse inputs while maintaining accuracy remains a critical challenge in 3D reconstruction. While advanced techniques like radiance fields and 3D Gaussian Splatting achieve rendering quality and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Chenlu Zhan , Yufei Zhang , Yu Lin , Gaoang Wang , Hongwei Wang

3D Gaussian Splatting (3DGS) renders pixels by rasterizing Gaussian primitives, where the rendering resolution and the primitive number, concluded as the optimization complexity, dominate the time cost in primitive optimization. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Youyu Chen , Junjun Jiang , Kui Jiang , Xiao Tang , Zhihao Li , Xianming Liu , Yinyu Nie

3D Gaussian Splatting (3DGS) has emerged as a mainstream for novel view synthesis, leveraging continuous aggregations of Gaussian functions to model scene geometry. However, 3DGS suffers from substantial memory requirements to store the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Yangming Zhang , Wenqi Jia , Wei Niu , Miao Yin

Rendering 3D surfaces has been revolutionized within the modeling of radiance fields through either 3DGS or NeRF. Although 3DGS has shown advantages over NeRF in terms of rendering quality or speed, there is still room for improvement in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Takeshi Noda , Yu-Shen Liu , Zhizhong Han