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3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the quality of reconstructions depends heavily on high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yiren Lu , Yunlai Zhou , Disheng Liu , Tuo Liang , Yu Yin

Recent 3D Gaussian Splatting (3DGS) representations have demonstrated remarkable performance in novel view synthesis; further, material-lighting disentanglement on 3DGS warrants relighting capabilities and its adaptability to broader…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Kai Ye , Chong Gao , Guanbin Li , Wenzheng Chen , Baoquan Chen

We introduce Gaussian-Flow, a novel point-based approach for fast dynamic scene reconstruction and real-time rendering from both multi-view and monocular videos. In contrast to the prevalent NeRF-based approaches hampered by slow training…

Computer Vision and Pattern Recognition · Computer Science 2023-12-07 Youtian Lin , Zuozhuo Dai , Siyu Zhu , Yao Yao

3D Gaussian Splatting (3DGS) has emerged as a prominent technique with the potential to become a mainstream method for 3D representations. It can effectively transform multi-view images into explicit 3D Gaussian through efficient training,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Yanqi Bao , Tianyu Ding , Jing Huo , Yaoli Liu , Yuxin Li , Wenbin Li , Yang Gao , Jiebo Luo

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

High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with handheld cameras. We present a method that adapts to camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Otto Seiskari , Jerry Ylilammi , Valtteri Kaatrasalo , Pekka Rantalankila , Matias Turkulainen , Juho Kannala , Esa Rahtu , Arno Solin

Modeling complex rigid motion across large spatiotemporal spans remains an unresolved challenge in dynamic reconstruction. Existing paradigms are mainly confined to short-term, small-scale deformation and offer limited consideration for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Yijun Xu , Jingrui Zhang , Yuhan Chen , Dingwen Wang , Lei Yu , Chu He

Representing and rendering dynamic scenes has been an important but challenging task. Especially, to accurately model complex motions, high efficiency is usually hard to guarantee. To achieve real-time dynamic scene rendering while also…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Guanjun Wu , Taoran Yi , Jiemin Fang , Lingxi Xie , Xiaopeng Zhang , Wei Wei , Wenyu Liu , Qi Tian , Xinggang Wang

Surgical reconstruction of dynamic tissues from endoscopic videos is a crucial technology in robot-assisted surgery. The development of Neural Radiance Fields (NeRFs) has greatly advanced deformable tissue reconstruction, achieving…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Wenfeng Huang , Xiangyun Liao , Yinling Qian , Hao Liu , Yongming Yang , Wenjing Jia , Qiong Wang

Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gaussian Splatting have achieved fine-grained reconstruction and high-fidelity novel view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Yuru Xiao , Zihan Lin , Chao Lu , Deming Zhai , Kui Jiang , Wenbo Zhao , Wei Zhang , Junjun Jiang , Huanran Wang , Xianming Liu

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

High-fidelity reconstruction of dynamic scenes is an important yet challenging problem. While recent 4D Gaussian Splatting (4DGS) has demonstrated the ability to model temporal dynamics, it couples Gaussian motion and geometric attributes…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yi Zhang , Yulei Kang , Jiangxin Sun , Beihao Xia , Jisheng Dang , Jian-Fang Hu

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

Reconstructing and editing 3D objects and scenes both play crucial roles in computer graphics and computer vision. Neural radiance fields (NeRFs) can achieve realistic reconstruction and editing results but suffer from inefficiency in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Tong Wu , Jia-Mu Sun , Yu-Kun Lai , Yuewen Ma , Leif Kobbelt , Lin Gao

The introduction of 3D Gaussian Splatting (3DGS) has advanced novel view synthesis by utilizing Gaussians to represent scenes. Encoding Gaussian point features with anchor embeddings has significantly enhanced the performance of newer 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Junyan Su , Baozhu Zhao , Xiaohan Zhang , Qi Liu

3D Gaussian Splatting (3DGS) is a recent approach for scene rendering. Although primarily designed for view synthesis, its potential for scene understanding tasks remains underexplored. In this work, we conduct a comparative evaluation of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Julia Farganus , Krzysztof Żurawicki , Arkadiusz Gaweł , Weronika Jakubowska , Halina Kwaśnicka

3D Gaussian Splatting (3DGS) has made significant strides in scene representation and neural rendering, with intense efforts focused on adapting it for dynamic scenes. Despite delivering remarkable rendering quality and speed, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Sangwoon Kwak , Joonsoo Kim , Jun Young Jeong , Won-Sik Cheong , Jihyong Oh , Munchurl Kim

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

Recent advancements in high-fidelity dynamic scene reconstruction have leveraged dynamic 3D Gaussians and 4D Gaussian Splatting for realistic scene representation. However, to make these methods viable for real-time applications such as…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Saqib Javed , Ahmad Jarrar Khan , Corentin Dumery , Chen Zhao , Mathieu Salzmann

Since its introduction, 3D Gaussian Splatting (3DGS) has rapidly transformed the landscape of 3D scene representations, inspiring an extensive body of associated research. Follow-up work includes analyses and contributions that enhance the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Bernhard Kerbl
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