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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

Recent advancements in generative video codec (GVC) typically encode video into a 2D latent grid and employ high-capacity generative decoders for reconstruction. However, this paradigm still leaves two key challenges in fully exploiting…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Zihan Zheng , Zhaoyang Jia , Naifu Xue , Jiahao Li , Bin Li , Zongyu Guo , Xiaoyi Zhang , Zhenghao Chen , Houqiang Li , Yan Lu

Previous surface reconstruction methods either suffer from low geometric accuracy or lengthy training times when dealing with real-world complex dynamic scenes involving multi-person activities, and human-object interactions. To tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shuo Wang , Binbin Huang , Ruoyu Wang , Shenghua Gao

We present latentSplat, a method to predict semantic Gaussians in a 3D latent space that can be splatted and decoded by a light-weight generative 2D architecture. Existing methods for generalizable 3D reconstruction either do not scale to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Christopher Wewer , Kevin Raj , Eddy Ilg , Bernt Schiele , Jan Eric Lenssen

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

Real-time immersive video communications, particularly high-fidelity 3D telepresence, necessitates a synergistic balance between instantaneous dynamic scene reconstruction and high-efficiency data transmission. While recent advancements in…

Image and Video Processing · Electrical Eng. & Systems 2026-04-29 Dingxi Yang , Wenqi Guo , Yue Liu , Jungong Han , Zhijin Qin

Recently, Gaussian Splatting methods have emerged as a desirable substitute for prior Radiance Field methods for novel-view synthesis of scenes captured with multi-view images or videos. In this work, we propose a novel extension to 4D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Karly Hou , Wanhua Li , Hanspeter Pfister

Image-based 3D generation has vast applications in robotics and gaming, where high-quality, diverse outputs and consistent 3D representations are crucial. However, existing methods have limitations: 3D diffusion models are limited by…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Ye Tao , Jiawei Zhang , Yahao Shi , Dongqing Zou , Bin Zhou

Continuous Spatio-Temporal Video Super-Resolution (C-STVSR) aims to simultaneously enhance the spatial resolution and frame rate of videos by arbitrary scale factors, offering greater flexibility than fixed-scale methods that are…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Mingyu Shi , Xin Di , Long Peng , Boxiang Cao , Anran Wu , Zhanfeng Feng , Jiaming Guo , Renjing Pei , Xueyang Fu , Yang Cao , Zhengjun Zha

Video Temporal Grounding (VTG) aims to localize the video segment that corresponds to a natural language query, which requires a comprehensive understanding of complex temporal dynamics. Existing Vision-LMMs typically perceive temporal…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Chaohong Guo , Yihan He , Yongwei Nie , Fei Ma , Xuemiao Xu , Chengjiang Long

We introduce the MAsked Generative VIdeo Transformer, MAGVIT, to tackle various video synthesis tasks with a single model. We introduce a 3D tokenizer to quantize a video into spatial-temporal visual tokens and propose an embedding method…

Computer Vision and Pattern Recognition · Computer Science 2023-04-06 Lijun Yu , Yong Cheng , Kihyuk Sohn , José Lezama , Han Zhang , Huiwen Chang , Alexander G. Hauptmann , Ming-Hsuan Yang , Yuan Hao , Irfan Essa , Lu Jiang

4D content generation has achieved remarkable progress recently. However, existing methods suffer from long optimization times, a lack of motion controllability, and a low quality of details. In this paper, we introduce DreamGaussian4D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Jiawei Ren , Liang Pan , Jiaxiang Tang , Chi Zhang , Ang Cao , Gang Zeng , Ziwei Liu

This paper aims to address the challenge of reconstructing long volumetric videos from multi-view RGB videos. Recent dynamic view synthesis methods leverage powerful 4D representations, like feature grids or point cloud sequences, to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Zhen Xu , Yinghao Xu , Zhiyuan Yu , Sida Peng , Jiaming Sun , Hujun Bao , Xiaowei Zhou

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

The advent of 3D Gaussian splatting (3DGS) has significantly enhanced the quality of volumetric video representation. Meanwhile, in contrast to conventional volumetric video, 3DGS video poses significant challenges for streaming due to its…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Han Gong , Qiyue Li , Zhi Liu , Hao Zhou , Peng Yuan Zhou , Zhu Li , Jie Li

In recent years, 3D Gaussian splatting has emerged as a powerful technique for 3D reconstruction and generation, known for its fast and high-quality rendering capabilities. To address these shortcomings, this paper introduces a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Xianglong He , Junyi Chen , Sida Peng , Di Huang , Yangguang Li , Xiaoshui Huang , Chun Yuan , Wanli Ouyang , Tong He

Free-Viewpoint Video (FVV) enables immersive 3D experiences, but efficient compression of dynamic 3D representation remains a major challenge. Existing dynamic 3D Gaussian Splatting methods couple reconstruction with optimization-dependent…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Wenkang Zhang , Yan Zhao , Qiang Wang , Zhixin Xu , Li Song , Zhengxue Cheng

3D Gaussian splatting video (3DGS) streaming has recently emerged as a research hotspot in both academia and industry, owing to its impressive ability to deliver immersive 3D video experiences. However, research in this area is still in its…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Han Gong , Qiyue Li , Jie Li , Zhi Liu

The computer vision and image processing research community has been involved in standardizing video data communications for the past many decades, leading to standards such as AVC, HEVC, VVC, AV1, AV2, etc. However, recent groundbreaking…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Lakshya Gupta , Imran N. Junejo

3D Gaussian Splatting represents a breakthrough in the field of novel view synthesis. It establishes Gaussians as core rendering primitives for highly accurate real-world environment reconstruction. Recent advances have drastically…

Graphics · Computer Science 2025-06-25 Jonathan Haberl , Philipp Fleck , Clemens Arth