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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

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 advanced radiance field reconstruction by enabling real-time rendering. However, its reliance on Gaussian kernels for geometry and low-order Spherical Harmonics (SH) for color encoding limits its ability to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Rong Liu , Dylan Sun , Meida Chen , Yue Wang , Andrew Feng

In the rapidly evolving field of 3D reconstruction, 3D Gaussian Splatting (3DGS) and 2D Gaussian Splatting (2DGS) represent significant advancements. Although 2DGS compresses 3D Gaussian primitives into 2D Gaussian surfels to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Zhuoxiao Li , Shanliang Yao , Yijie Chu , Angel F. Garcia-Fernandez , Yong Yue , Eng Gee Lim , Xiaohui Zhu

3D Gaussian splatting models, as a novel explicit 3D representation, have been applied in many domains recently, such as explicit geometric editing and geometry generation. Progress has been rapid. However, due to their mixed scales and…

Graphics · Computer Science 2024-03-15 Qiyuan Feng , Gengchen Cao , Haoxiang Chen , Tai-Jiang Mu , Ralph R. Martin , Shi-Min Hu

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for generating photorealistic renderings of a scene in real-time. However, the volumetric nature of 3DGS limits its ability to accurately capture surface geometry. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Prajwal Gupta C. R. , Divyam Sheth , Jinjoo Ha , Mirela Ostrek , Justus Thies

3D Gaussian Splatting (3DGS) has attracted great attention in novel view synthesis because of its superior rendering efficiency and high fidelity. However, the trained Gaussians suffer from severe zooming degradation due to non-adjustable…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Jiameng Li , Yue Shi , Jiezhang Cao , Bingbing Ni , Wenjun Zhang , Kai Zhang , Luc Van Gool

We present a novel approach for enhancing the resolution and geometric fidelity of 3D Gaussian Splatting (3DGS) beyond native training resolution. Current 3DGS methods are fundamentally limited by their input resolution, producing…

Graphics · Computer Science 2025-06-10 Shuja Khalid , Mohamed Ibrahim , Yang Liu

3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, a key requirement for immersive applications. However, the extension of 3DGS to dynamic scenes remains limitations on the substantial data volume of dense Gaussians and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Jiayu Yang , Weijian Su , Songqian Zhang , Yuqi Han , Jinli Suo , Qiang Zhang

3D Gaussian Splatting (3DGS) has emerged as a powerful approach for 3D scene reconstruction using 3D Gaussians. However, neither the centers nor surfaces of the Gaussians are accurately aligned to the object surface, complicating their…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Miriam Jäger , Markus Hillemann , Boris Jutzi

While 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction, it suffers from significant overhead due to massive redundant primitives. Existing compression methods typically rely on local sampling or fixed pruning thresholds,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Beizhen Zhao , Sicheng Yu , Ziran Yin , Dongxu Shen , Hao Wang

The advent of 3D Gaussian Splatting (3DGS) has recently brought about a revolution in the field of neural rendering, facilitating high-quality renderings at real-time speed. However, 3DGS heavily depends on the initialized point cloud…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Kai Cheng , Xiaoxiao Long , Kaizhi Yang , Yao Yao , Wei Yin , Yuexin Ma , Wenping Wang , Xuejin Chen

In this paper, we address common error sources for 3D Gaussian Splatting (3DGS) including blur, imperfect camera poses, and color inconsistencies, with the goal of improving its robustness for practical applications like reconstructions…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 François Darmon , Lorenzo Porzi , Samuel Rota-Bulò , Peter Kontschieder

Recent advances in novel view synthesis have demonstrated impressive results in fast photorealistic scene rendering through differentiable point rendering, either via Gaussian Splatting (3DGS) [Kerbl and Kopanas et al. 2023] or neural point…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Linus Franke , Laura Fink , Marc Stamminger

Generalizable 3D Gaussian Splatting reconstruction showcases advanced Image-to-3D content creation but requires substantial computational resources and large datasets, posing challenges to training models from scratch. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Xiufeng Huang , Ka Chun Cheung , Runmin Cong , Simon See , Renjie Wan

While 3D Gaussian Splatting (3DGS) enables high-quality, real-time rendering for bounded scenes, its extension to large-scale urban environments gives rise to critical challenges in terms of geometric consistency, memory efficiency, and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Changbai Li , Haodong Zhu , Hanlin Chen , Xiuping Liang , Tongfei Chen , Shuwei Shao , Linlin Yang , Huobin Tan , Baochang Zhang

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh

3D Gaussian Splatting (3DGS) achieves high-fidelity rendering with fast real-time performance, but existing methods rely on offline training after full Structure-from-Motion (SfM) processing. In contrast, this work introduces Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Yiwei Xu , Yifei Yu , Wentian Gan , Tengfei Wang , Zongqian Zhan , Hao Cheng , Xin Wang

3D Gaussian Splatting (3DGS) has shown convincing performance in rendering speed and fidelity, yet the generation of Gaussian Splatting remains a challenge due to its discreteness and unstructured nature. In this work, we propose DiffGS, a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Junsheng Zhou , Weiqi Zhang , Yu-Shen Liu

3D Gaussian Splatting (3D-GS) has emerged as a significant advancement in the field of Computer Graphics, offering explicit scene representation and novel view synthesis without the reliance on neural networks, such as Neural Radiance…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Ben Fei , Jingyi Xu , Rui Zhang , Qingyuan Zhou , Weidong Yang , Ying He