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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

Immersive video offers a 6-Dof-free viewing experience, potentially playing a key role in future video technology. Recently, 4D Gaussian Splatting has gained attention as an effective approach for immersive video due to its high rendering…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Hao Li , Sicheng Li , Xiang Gao , Abudouaihati Batuer , Lu Yu , Yiyi Liao

Implicit neural representations (INRs) recently achieved great success in image representation and compression, offering high visual quality and fast rendering speeds with 10-1000 FPS, assuming sufficient GPU resources are available.…

Image and Video Processing · Electrical Eng. & Systems 2024-07-10 Xinjie Zhang , Xingtong Ge , Tongda Xu , Dailan He , Yan Wang , Hongwei Qin , Guo Lu , Jing Geng , Jun Zhang

Recent advances in 3D Gaussian Splatting (3DGS) have enabled fast, photorealistic rendering of dynamic 3D scenes, showing strong potential in immersive communication. However, in digital human encoding and transmission, the compression…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Haocheng Tang , Ruoke Yan , Xinhui Yin , Qi Zhang , Xinfeng Zhang , Siwei Ma , Wen Gao , Chuanmin Jia

Efficient neural representations for dynamic video scenes are critical for applications ranging from video compression to interactive simulations. Yet, existing methods often face challenges related to high memory usage, lengthy training…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Andrew Bond , Jui-Hsien Wang , Long Mai , Erkut Erdem , Aykut Erdem

Implicit Neural Representation for Videos (NeRV) has introduced a novel paradigm for video representation and compression, outperforming traditional codecs. As model size grows, however, slow encoding and decoding speed and high memory…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Inseo Lee , Youngyoon Choi , Joonseok Lee

High-fidelity rendering of dynamic humans from monocular videos typically degrades catastrophically under occlusions. Existing solutions incorporate external priors-either hallucinating missing content via generative models, which induces…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Weiquan Wang , Feifei Shao , Lin Li , Zhen Wang , Jun Xiao , Long Chen

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time, high-performance rendering, enabling a wide range of applications. However, representing 3D scenes with numerous explicit Gaussian primitives imposes…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Joo Chan Lee , Jong Hwan Ko , Eunbyung Park

Realistic 3D human generation from text prompts is a desirable yet challenging task. Existing methods optimize 3D representations like mesh or neural fields via score distillation sampling (SDS), which suffers from inadequate fine details…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Xian Liu , Xiaohang Zhan , Jiaxiang Tang , Ying Shan , Gang Zeng , Dahua Lin , Xihui Liu , Ziwei Liu

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) has emerged as an efficient and high-fidelity paradigm for novel view synthesis. To adapt 3DGS for dynamic content, deformable 3DGS incorporates temporally deformable primitives with learnable latent embeddings…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Mufan Liu , Qi Yang , He Huang , Wenjie Huang , Zhenlong Yuan , Zhu Li , Yiling Xu

Despite significant advancements in dynamic neural rendering, existing methods fail to address the unique challenges posed by UAV-captured scenarios, particularly those involving monocular camera setups, top-down perspective, and multiple…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Jaehoon Choi , Dongki Jung , Christopher Maxey , Yonghan Lee , Sungmin Eum , Dinesh Manocha , Heesung Kwon

The online reconstruction of dynamic scenes from multi-view streaming videos faces significant challenges in training, rendering and storage efficiency. Harnessing superior learning speed and real-time rendering capabilities, 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Qiankun Gao , Jiarui Meng , Chengxiang Wen , Jie Chen , Jian Zhang

Dynamic scene reconstruction poses a persistent challenge in 3D vision. Deformable 3D Gaussian Splatting has emerged as an effective method for this task, offering real-time rendering and high visual fidelity. This approach decomposes a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Bing He , Yunuo Chen , Guo Lu , Qi Wang , Qunshan Gu , Rong Xie , Li Song , Wenjun Zhang

We present a novel animatable 3D Gaussian model for rendering high-fidelity free-view human motions in real time. Compared to existing NeRF-based methods, the model owns better capability in synthesizing high-frequency details without the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Keyang Ye , Tianjia Shao , Kun Zhou

We have recently seen great progress in 3D scene reconstruction through explicit point-based 3D Gaussian Splatting (3DGS), notable for its high quality and fast rendering speed. However, reconstructing dynamic scenes such as complex human…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Chao Zhang , Yifeng Zhou , Shuheng Wang , Wenfa Li , Degang Wang , Yi Xu , Shaohui Jiao

Rendering realistic human-object interactions (HOIs) from sparse-view inputs is a challenging yet crucial task for various real-world applications. Existing methods often struggle to simultaneously achieve high rendering quality, physical…

Graphics · Computer Science 2026-04-10 Weiquan Wang , Jun Xiao , Yi Yang , Yueting Zhuang , Long Chen

3D Gaussian Splatting (3DGS) has substantial potential for enabling photorealistic Free-Viewpoint Video (FVV) experiences. However, the vast number of Gaussians and their associated attributes poses significant challenges for storage and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Qiang Hu , Zihan Zheng , Houqiang Zhong , Sihua Fu , Li Song , XiaoyunZhang , Guangtao Zhai , Yanfeng Wang

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

3D Gaussian Splatting (3DGS) revolutionized novel view rendering. Instead of inferring from dense spatial points, as implicit representations do, 3DGS uses sparse Gaussians. This enables real-time performance but increases space…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Cem Eteke , Enzo Tartaglione