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Related papers: Instruct-4DGS: Efficient Dynamic Scene Editing via…

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We present Inst4DGS, an instance-decomposed 4D Gaussian Splatting (4DGS) approach with long-horizon per-Gaussian trajectories. While dynamic 4DGS has advanced rapidly, instance-decomposed 4DGS remains underexplored, largely due to the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Yonghan Lee , Dinesh Manocha

Novel view synthesis of dynamic scenes is becoming important in various applications, including augmented and virtual reality. We propose a novel 4D Gaussian Splatting (4DGS) algorithm for dynamic scenes from casually recorded monocular…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Mijeong Kim , Jongwoo Lim , Bohyung Han

Dynamic extensions of 3D Gaussian Splatting (3DGS) achieve high-quality reconstructions through neural motion fields, but per-Gaussian neural inference makes these models computationally expensive. Building on DeformableGS, we introduce…

Graphics · Computer Science 2026-03-31 Allen Tu , Haiyang Ying , Alex Hanson , Yonghan Lee , Tom Goldstein , Matthias Zwicker

Persistent dynamic scene modeling for tracking and novel-view synthesis remains challenging due to the difficulty of capturing accurate deformations while maintaining computational efficiency. We propose SCas4D, a cascaded optimization…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Jipeng Lyu , Jiahua Dong , Yu-Xiong Wang

We present DeSiRe-GS, a self-supervised gaussian splatting representation, enabling effective static-dynamic decomposition and high-fidelity surface reconstruction in complex driving scenarios. Our approach employs a two-stage optimization…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Chensheng Peng , Chengwei Zhang , Yixiao Wang , Chenfeng Xu , Yichen Xie , Wenzhao Zheng , Kurt Keutzer , Masayoshi Tomizuka , Wei Zhan

Generating dynamic 3D object from a single-view video is challenging due to the lack of 4D labeled data. An intuitive approach is to extend previous image-to-3D pipelines by transferring off-the-shelf image generation models such as score…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Zijie Pan , Zeyu Yang , Xiatian Zhu , Li Zhang

Reconstructing dynamic scenes from Vehicle-to-Infrastructure Cooperative Autonomous Driving (VICAD) data is fundamentally complicated by temporal asynchrony: vehicle and infrastructure cameras operate on independent clocks, capturing the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Yulong Chen , Xiaoyun Dong , Haoyu Zhang , Zongxian Yang , Lewei Xie , Xinke Li , Yifan Zhang , Kai Wang , Jianping Wang

Editing objects within a scene is a critical functionality required across a broad spectrum of applications in computer vision and graphics. As 3D Gaussian Splatting (3DGS) emerges as a frontier in scene representation, the effective…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Teng Xu , Jiamin Chen , Peng Chen , Youjia Zhang , Junqing Yu , Wei Yang

Modern 3D engines and graphics pipelines require mesh as a memory-efficient representation, which allows efficient rendering, geometry processing, texture editing, and many other downstream operations. However, it is still highly difficult…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Isabella Liu , Hao Su , Xiaolong Wang

Reconstructing intricate, ever-changing environments remains a central ambition in computer vision, yet existing solutions often crumble before the complexity of real-world dynamics. We present DynaSplat, an approach that extends Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Junli Deng , Ping Shi , Qipei Li , Jinyang Guo

Reconstructing large-scale dynamic scenes from visual observations is a fundamental challenge in computer vision, with critical implications for robotics and autonomous systems. While recent differentiable rendering methods such as Neural…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Jingkang Wang , Henry Che , Yun Chen , Ze Yang , Lily Goli , Sivabalan Manivasagam , Raquel Urtasun

Recent advances in text-driven 3D scene editing and stylization, which leverage the powerful capabilities of 2D generative models, have demonstrated promising outcomes. However, challenges remain in ensuring high-quality stylization and…

Graphics · Computer Science 2026-03-03 Haruo Fujiwara , Yusuke Mukuta , Tatsuya Harada

Dynamic scene reconstruction has garnered significant attention in recent years due to its capabilities in high-quality and real-time rendering. Among various methodologies, constructing a 4D spatial-temporal representation, such as 4D-GS,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Weiwei Cai , Weicai Ye , Peng Ye , Tong He , Tao Chen

4D generation has made remarkable progress in synthesizing dynamic 3D objects from input text, images, or videos. However, existing methods often represent motion as an implicit deformation field, which limits direct control and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-05 Lifan Wu , Ruijie Zhu , Yubo Ai , Tianzhu Zhang

Existing 4D Gaussian Splatting methods rely on per-Gaussian deformation from a canonical space to target frames, which overlooks redundancy among adjacent Gaussian primitives and results in suboptimal performance. To address this…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 He Huang , Qi Yang , Mufan Liu , Yiling Xu , Zhu Li

We introduce G-Style, a novel algorithm designed to transfer the style of an image onto a 3D scene represented using Gaussian Splatting. Gaussian Splatting is a powerful 3D representation for novel view synthesis, as -- compared to other…

Graphics · Computer Science 2024-09-06 Áron Samuel Kovács , Pedro Hermosilla , Renata G. Raidou

3D scene understanding has become an essential area of research with applications in autonomous driving, robotics, and augmented reality. Recently, 3D Gaussian Splatting (3DGS) has emerged as a powerful approach, combining explicit modeling…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Haijie Li , Yanmin Wu , Jiarui Meng , Qiankun Gao , Zhiyao Zhang , Ronggang Wang , Jian Zhang

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

Dynamic 4D Gaussian Splatting (4DGS) effectively extends the high-speed rendering capabilities of 3D Gaussian Splatting (3DGS) to represent volumetric videos. However, the large number of Gaussians, substantial temporal redundancies, and…

Graphics · Computer Science 2026-01-14 Hyeongmin Lee , Kyungjune Baek

Minimally invasive surgery (MIS) requires high-fidelity, real-time visual feedback of dynamic and low-texture surgical scenes. To address these requirements, we introduce FeatureEndo-4DGS (FE-4DGS), the first real time pipeline leveraging…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Kai Li , Junhao Wang , William Han , Ding Zhao