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Reconstructing and understanding 3D scenes from unposed sparse views in a feed-forward manner remains as a challenging task in 3D computer vision. Recent approaches use per-pixel 3D Gaussian Splatting for reconstruction, followed by a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Honggyu An , Jaewoo Jung , Mungyeom Kim , Chaehyun Kim , Minkyeong Jeon , Jisang Han , Kazumi Fukuda , Takuya Narihira , Hyuna Ko , Junsu Kim , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

As 3D Gaussian Splatting (3DGS) provides fast and high-quality novel view synthesis, it is a natural extension to deform a canonical 3DGS to multiple frames for representing a dynamic scene. However, previous works fail to accurately…

Computer Vision and Pattern Recognition · Computer Science 2024-07-29 Jeongmin Bae , Seoha Kim , Youngsik Yun , Hahyun Lee , Gun Bang , Youngjung Uh

3D Gaussian Splatting (3DGS) has emerged as a promising 3D reconstruction technique. The traditional 3DGS training pipeline follows three sequential steps: Gaussian densification, Gaussian projection, and color splatting. Despite its…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Junyi Wu , Jiaming Xu , Jinhao Li , Yongkang Zhou , Jiayi Pan , Xingyang Li , Guohao Dai

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

While 3D Gaussian Splatting (3DGS) excels in static scene modeling, its extension to dynamic scenes introduces significant challenges. Existing dynamic 3DGS methods suffer from either over-smoothing due to low-rank decomposition or feature…

Graphics · Computer Science 2025-08-08 Yifan Zhou , Beizhen Zhao , Pengcheng Wu , Hao Wang

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

Real-time rendering of dynamic scenes with view-dependent effects remains a fundamental challenge in computer graphics. While recent advances in Gaussian Splatting have shown promising results separately handling dynamic scenes (4DGS) and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu

3D Gaussian Splatting (3DGS) has demonstrated its advantages in achieving fast and high-quality rendering. As point clouds serve as a widely-used and easily accessible form of 3D representation, bridging the gap between point clouds and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Weiqi Zhang , Junsheng Zhou , Haotian Geng , Wenyuan Zhang , Yu-Shen Liu

3D scene representations have gained immense popularity in recent years. Methods that use Neural Radiance fields are versatile for traditional tasks such as novel view synthesis. In recent times, some work has emerged that aims to extend…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Shijie Zhou , Haoran Chang , Sicheng Jiang , Zhiwen Fan , Zehao Zhu , Dejia Xu , Pradyumna Chari , Suya You , Zhangyang Wang , Achuta Kadambi

3D Gaussian Splatting (3DGS) has emerged as a state-of-the-art method for novel view synthesis. However, its performance heavily relies on dense, high-quality input imagery, an assumption that is often violated in real-world applications,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Zhankuo Xu , Chaoran Feng , Yingtao Li , Jianbin Zhao , Jiashu Yang , Wangbo Yu , Li Yuan , Yonghong Tian

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

3D Gaussian Splatting (3DGS) has emerged as a promising approach for 3D scene representation, offering a reduction in computational overhead compared to Neural Radiance Fields (NeRF). However, 3DGS is susceptible to high-frequency artifacts…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Shen Chen , Jiale Zhou , Lei Li

Text-to-3D asset generation has achieved significant optimization under the supervision of 2D diffusion priors. However, when dealing with compositional scenes, existing methods encounter several challenges: 1). failure to ensure that…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Qixuan Li , Chao Wang , Zongjin He , Yan Peng

3D Gaussian Splatting (3DGS) has emerged as a real-time, differentiable representation for neural scene understanding. However, existing 3DGS-based methods struggle to represent hierarchical 3D semantic structures and capture whole-part…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jingbin You , Zehao Li , Hao Jiang , Xinzhu Ma , Shuqin Gao , Honglong Zhao , Congcong Zheng , Tianlu Mao , Feng Dai , Yucheng Zhang , Zhaoqi Wang

3D modeling of highly reflective objects remains challenging due to strong view-dependent appearances. While previous SDF-based methods can recover high-quality meshes, they are often time-consuming and tend to produce over-smoothed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Jinguang Tong , Xuesong li , Fahira Afzal Maken , Sundaram Muthu , Lars Petersson , Chuong Nguyen , Hongdong Li

3D Gaussian Splatting (3DGS) has emerged as a leading approach for high-quality novel view synthesis, with numerous variants extending its applicability to a broad spectrum of 3D and 4D scene reconstruction tasks. Despite its success, the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yiming Wang , Shaofei Wang , Marko Mihajlovic , Siyu Tang

3D Gaussian Splatting (3DGS) techniques have achieved satisfactory 3D scene representation. Despite their impressive performance, they confront challenges due to the limitation of structure-from-motion (SfM) methods on acquiring accurate…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Ao Gao , Luosong Guo , Tao Chen , Zhao Wang , Ying Tai , Jian Yang , Zhenyu Zhang

User-friendly 3D object editing is a challenging task that has attracted significant attention recently. The limitations of direct 3D object editing without 2D prior knowledge have prompted increased attention towards utilizing 2D…

Graphics · Computer Science 2024-05-10 Sitian Shen , Jing Xu , Yuheng Yuan , Xingyi Yang , Qiuhong Shen , Xinchao Wang

3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking. However, 3DGS fails to accurately represent surfaces due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Binbin Huang , Zehao Yu , Anpei Chen , Andreas Geiger , Shenghua Gao

3D Gaussian Splatting (3DGS) has become an emerging tool for dynamic scene reconstruction. However, existing methods focus mainly on extending static 3DGS into a time-variant representation, while overlooking the rich motion information…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhiyang Guo , Wengang Zhou , Li Li , Min Wang , Houqiang Li