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Related papers: RiGS: Rigid-aware 4D Gaussian Splatting from a Sin…

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3D Gaussian Splatting (3DGS) demonstrates unparalleled superior performance in 3D scene reconstruction. However, 3DGS heavily relies on the sharp images. Fulfilling this requirement can be challenging in real-world scenarios especially when…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Yijia Guo , Liwen Hu , Yuanxi Bai , Jiawei Yao , Lei Ma , Tiejun Huang

Novel view synthesis from monocular videos of dynamic scenes with unknown camera poses remains a fundamental challenge in computer vision and graphics. While recent advances in 3D representations such as Neural Radiance Fields (NeRF) and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Mengqi Guo , Bo Xu , Yanyan Li , Gim Hee Lee

Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an essential component for intelligent systems. Recent approaches have improved temporal coherence…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Melonie de Almeida , Daniela Ivanova , Tong Shi , John H. Williamson , Paul Henderson

We present VIGS-SLAM, a visual-inertial 3D Gaussian Splatting SLAM system that achieves robust real-time tracking and high-fidelity reconstruction. Although recent 3DGS-based SLAM methods achieve dense and photorealistic mapping, their…

Robotics · Computer Science 2026-03-16 Zihan Zhu , Wei Zhang , Moyang Li , Norbert Haala , Marc Pollefeys , Daniel Barath

Egocentric video provides a unique view into human perception and interaction, with growing relevance for augmented reality, robotics, and assistive technologies. However, rapid camera motion and complex scene dynamics pose major challenges…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Jan Warchocki , Xi Wang , Jonas Kulhanek , Jan van Gemert

Recent advances in 3D Gaussian Splatting (3DGS) deliver striking photorealism, and extending it to large scenes opens new opportunities for semantic reasoning and prediction in applications such as autonomous driving. Today's…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Shengkai Zhang , Yuhe Liu , Jianhua He , Xuedou Xiao , Mozi Chen , Kezhong Liu

We present DrivingGaussian, an efficient and effective framework for surrounding dynamic autonomous driving scenes. For complex scenes with moving objects, we first sequentially and progressively model the static background of the entire…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Xiaoyu Zhou , Zhiwei Lin , Xiaojun Shan , Yongtao Wang , Deqing Sun , Ming-Hsuan Yang

Monocular dynamic reconstruction is a challenging and long-standing vision problem due to the highly ill-posed nature of the task. Existing approaches depend on templates, are effective only in quasi-static scenes, or fail to model 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Qianqian Wang , Vickie Ye , Hang Gao , Weijia Zeng , Jake Austin , Zhengqi Li , Angjoo Kanazawa

Novel view synthesis for dynamic scenes is still a challenging problem in computer vision and graphics. Recently, Gaussian splatting has emerged as a robust technique to represent static scenes and enable high-quality and real-time novel…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Yi-Hua Huang , Yang-Tian Sun , Ziyi Yang , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi

Dynamic view synthesis has seen significant advances, yet reconstructing scenes from uncalibrated, casual video remains challenging due to slow optimization and complex parameter estimation. In this work, we present Instant4D, a monocular…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Zhanpeng Luo , Haoxi Ran , Li Lu

In this paper, we propose UniGS, a unified map representation and differentiable framework for high-fidelity multimodal 3D reconstruction based on 3D Gaussian Splatting. Our framework integrates a CUDA-accelerated rasterization pipeline…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Yusen Xie , Zhenmin Huang , Jianhao Jiao , Dimitrios Kanoulas , Jun Ma

Accurate 3D reconstruction of dynamic surgical scenes from endoscopic video is essential for robotic-assisted surgery. While recent 3D Gaussian Splatting methods have shown promise in achieving high-quality reconstructions with fast…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Jialei Chen , Xin Zhang , Mobarakol Islam , Francisco Vasconcelos , Danail Stoyanov , Daniel S. Elson , Baoru Huang

In this paper, we aim to jointly model the geometry, appearance, and physical information of 3D scenes solely from dynamic multi-view videos, without relying on any physical priors. Existing works typically employ physical losses merely as…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Nengbo Lu , Bin Zhao

3D Gaussian splats have emerged as a revolutionary, effective, learned representation for static 3D scenes. In this work, we explore using 2D Gaussian splats as a new primitive for representing videos. We propose GSVC, an approach to…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Longan Wang , Yuang Shi , Wei Tsang Ooi

The recent surge in 4D Gaussian Splatting (4DGS) has achieved impressive dynamic scene reconstruction. While these methods demonstrate remarkable performance, the specific drivers behind such gains remain less explored, making a systematic…

Computer Vision and Pattern Recognition · Computer Science 2026-05-06 Lucas Yunkyu Lee , Soonho Kim , Youngwook Kim , Sangmin Kim , Jaesik Park

While 3D Gaussian Splatting (3DGS) excels in static scene modeling, its extension to dynamic scenes introduces significant challenges. Existing dynamic 3DGS methods suffer from either over-smoothing due to low-rank decomposition or feature…

Graphics · Computer Science 2025-08-08 Yifan Zhou , Beizhen Zhao , Pengcheng Wu , Hao Wang

3D Gaussian Splatting (3DGS) has emerged as a novel explicit representation for 3D scenes, offering both high-fidelity reconstruction and efficient rendering. However, 3DGS lacks 3D segmentation ability, which limits its applicability in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Yupeng Zhang , Dezhi Zheng , Ping Lu , Han Zhang , Lei Wang , Liping xiang , Cheng Luo , Kaijun Deng , Xiaowen Fu , Linlin Shen , Jinbao Wang

We present a dynamic reconstruction system that receives a casual monocular RGB video as input, and outputs a complete and persistent reconstruction of the scene. In other words, we reconstruct not only the the currently visible parts of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Kirill Mazur , Marwan Taher , Andrew J. Davison

3D reconstruction and simulation, although interrelated, have distinct objectives: reconstruction requires a flexible 3D representation that can adapt to diverse scenes, while simulation needs a structured representation to model motion…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Shaojie Ma , Yawei Luo , Wei Yang , Yi Yang

A spike camera is a specialized high-speed visual sensor that offers advantages such as high temporal resolution and high dynamic range compared to conventional frame cameras. These features provide the camera with significant advantages in…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Jinze Yu , Xin Peng , Zhengda Lu , Laurent Kneip , Yiqun Wang