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Maintaining consistent 3D scene representations over time is a significant challenge in computer vision. Updating 3D scenes from sparse-view observations is crucial for various real-world applications, including urban planning, disaster…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Zeyuan An , Yanghang Xiao , Zhiying Leng , Frederick W. B. Li , Xiaohui Liang

Dynamic and static components in scenes often exhibit distinct properties, yet most 4D reconstruction methods treat them indiscriminately, leading to suboptimal performance in both cases. This work introduces SDD-4DGS, the first framework…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Dai Sun , Huhao Guan , Kun Zhang , Xike Xie , S. Kevin Zhou

Reconstructing 3D vessel structures from sparse-view dynamic digital subtraction angiography (DSA) images enables accurate medical assessment while reducing radiation exposure. Existing methods often produce suboptimal results or require…

Image and Video Processing · Electrical Eng. & Systems 2025-03-27 Zhentao Liu , Ruyi Zha , Huangxuan Zhao , Hongdong Li , Zhiming Cui

The advent of 3D Gaussian Splatting (3D-GS) techniques and their dynamic scene modeling variants, 4D-GS, offers promising prospects for real-time rendering of dynamic surgical scenarios. However, the prerequisite for modeling dynamic scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Hengyu Liu , Yifan Liu , Chenxin Li , Wuyang Li , Yixuan Yuan

Topology-consistent dynamic model sequences are essential for applications such as animation and model editing. However, existing 4D reconstruction methods face challenges in generating high-quality topology-consistent meshes. To address…

Graphics · Computer Science 2025-12-02 Hanzhi Guo , Dongdong Weng , Mo Su , Yixiao Chen , Xiaonuo Dongye , Chenyu Xu

We introduce Mono4DGS-HDR, the first system for reconstructing renderable 4D high dynamic range (HDR) scenes from unposed monocular low dynamic range (LDR) videos captured with alternating exposures. To tackle such a challenging problem, we…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Jinfeng Liu , Lingtong Kong , Mi Zhou , Jinwen Chen , Dan Xu

In this paper, we present a novel framework for video-to-4D generation that creates high-quality dynamic 3D content from single video inputs. Direct 4D diffusion modeling is extremely challenging due to costly data construction and the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Bowen Zhang , Sicheng Xu , Chuxin Wang , Jiaolong Yang , Feng Zhao , Dong Chen , Baining Guo

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

Common computer vision systems typically assume ideal pinhole cameras but fail when facing real-world camera effects such as fisheye distortion and rolling shutter, mainly due to the lack of learning from training data with camera effects.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Yi-Ruei Liu , You-Zhe Xie , Yu-Hsiang Hsu , I-Sheng Fang , Yu-Lun Liu , Jun-Cheng Chen

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the first approach combining event cameras, which capture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Wenhao Xu , Wenming Weng , Yueyi Zhang , Ruikang Xu , Zhiwei Xiong

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling scenes affected by transient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Chuanyu Fu , Yuqi Zhang , Kunbin Yao , Guanying Chen , Yuan Xiong , Chuan Huang , Shuguang Cui , Xiaochun Cao

We present SS4D, a native 4D generative model that synthesizes dynamic 3D objects directly from monocular video. Unlike prior approaches that construct 4D representations by optimizing over 3D or video generative models, we train a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Zhibing Li , Mengchen Zhang , Tong Wu , Jing Tan , Jiaqi Wang , Dahua Lin

In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\times$4k pixels) is hindered by the excessive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Wenkai Liu , Tao Guan , Bin Zhu , Lili Ju , Zikai Song , Dan Li , Yuesong Wang , Wei Yang

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

Volumetric video has emerged as a key medium for immersive telepresence and augmented/virtual reality, enabling six-degrees-of-freedom (6DoF) navigation and realistic spatial interactions. However, delivering high-quality dynamic volumetric…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Houqiang Zhong , Zihan Zheng , Qiang Hu , Yuan Tian , Ning Cao , Lan Xu , Xiaoyun Zhang , Zhengxue Cheng , Li Song , Wenjun Zhang

Modeling the time-varying 3D appearance of plants during growth poses unique challenges: unlike most dynamic scenes, plants continuously generate new geometry as they expand, branch, and differentiate. Existing dynamic scene representations…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Weihan Luo , Lily Goli , Sherwin Bahmani , Felix Taubner , Andrea Tagliasacchi , David B. Lindell

Current generative models struggle to synthesize dynamic 4D driving scenes that simultaneously support temporal extrapolation and spatial novel view synthesis (NVS) without per-scene optimization. A key challenge lies in finding an…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Jiazhe Guo , Yikang Ding , Xiwu Chen , Shuo Chen , Bohan Li , Yingshuang Zou , Xiaoyang Lyu , Feiyang Tan , Xiaojuan Qi , Zhiheng Li , Hao Zhao

Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent efforts alleviate this issue by enhancing multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jimin Tang , Wenyuan Zhang , Junsheng Zhou , Zian Huang , Kanle Shi , Shenkun Xu , Yu-Shen Liu , Zhizhong Han

Recently, Gaussian splatting has received more and more attention in the field of static scene rendering. Due to the low computational overhead and inherent flexibility of explicit representations, plane-based explicit methods are popular…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Jiawei Xu , Zexin Fan , Jian Yang , Jin Xie

Current 4D Gaussian frameworks for dynamic scene reconstruction deliver impressive visual fidelity and rendering speed, however, the inherent trade-off between storage costs and the ability to characterize complex physical motions…

Graphics · Computer Science 2025-07-11 Wei Yao , Shuzhao Xie , Letian Li , Weixiang Zhang , Zhixin Lai , Shiqi Dai , Ke Zhang , Zhi Wang
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