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This paper focuses on a challenging setting of simultaneously modeling geometry and appearance of hand-object interaction scenes without any object priors. We follow the trend of dynamic 3D Gaussian Splatting based methods, and address…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hao Tian , Chenyangguang Zhang , Rui Liu , Wen Shen , Xiaolin Qin

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

Recently, 3D Gaussian Splatting (3DGS), an explicit scene representation technique, has shown significant promise for dynamic novel-view synthesis from monocular video input. However, purely data-driven 3DGS often struggles to capture the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Haoqin Hong , Ding Fan , Fubin Dou , Zhi-Li Zhou , Haoran Sun , Congcong Zhu , Jingrun Chen

The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Traditional methods relying on dense point clouds and triangular meshes struggle with moving…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peizhen Zheng , Dongjing Jiang , Qingchong Jiao , Redouane EL Bouchtaoui , Flynnwell Jianfei Zhang

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

Reconstructing and simulating elastic objects from visual observations is crucial for applications in computer vision and robotics. Existing methods, such as 3D Gaussians, model 3D appearance and geometry, but lack the ability to estimate…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Licheng Zhong , Hong-Xing Yu , Jiajun Wu , Yunzhu Li

Reconstructing urban scenes is challenging due to their complex geometries and the presence of potentially dynamic objects. 3D Gaussian Splatting (3DGS)-based methods have shown strong performance, but existing approaches often incorporate…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Ziwen Li , Jiaxin Huang , Runnan Chen , Yunlong Che , Yandong Guo , Tongliang Liu , Fakhri Karray , Mingming Gong

In this paper, we aim to model 3D scene geometry, appearance, and physical information just from dynamic multi-view videos in the absence of any human labels. By leveraging physics-informed losses as soft constraints or integrating simple…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Jinxi Li , Ziyang Song , Bo Yang

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

3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis performance. While conventional methods require per-scene optimization, more recently several feed-forward methods have been proposed to generate pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Shengjun Zhang , Xin Fei , Fangfu Liu , Haixu Song , Yueqi Duan

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

Dynamic scene reconstruction is a long-term challenge in 3D vision. Recent methods extend 3D Gaussian Splatting to dynamic scenes via additional deformation fields and apply explicit constraints like motion flow to guide the deformation.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 DaDong Jiang , Zhihui Ke , Xiaobo Zhou , Zhi Hou , Xianghui Yang , Wenbo Hu , Tie Qiu , Chunchao Guo

3D Gaussian Splatting (3DGS) has become a competitive approach for novel view synthesis (NVS) due to its advanced rendering efficiency through 3D Gaussian projection and blending. However, Gaussians are treated equally weighted for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Zhihao Guo , Peng Wang , Zidong Chen , Xiangyu Kong , Yan Lyu , Guanyu Gao , Liangxiu Han

Understanding dynamic scenes from casual videos is critical for scalable robot learning, yet four-dimensional (4D) reconstruction under strictly monocular settings remains highly ill-posed. To address this challenge, our key insight is that…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Can Li , Jie Gu , Jingmin Chen , Fangzhou Qiu , Lei Sun

Photorealistic 3D reconstruction of street scenes is a critical technique for developing real-world simulators for autonomous driving. Despite the efficacy of Neural Radiance Fields (NeRF) for driving scenes, 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Nan Huang , Xiaobao Wei , Wenzhao Zheng , Pengju An , Ming Lu , Wei Zhan , Masayoshi Tomizuka , Kurt Keutzer , Shanghang Zhang

3D Gaussian Splatting (3DGS) has gained significant attention due to its high-quality novel view rendering, motivating research to address real-world challenges. A critical issue is the camera motion blur caused by movement during exposure,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jungho Lee , Donghyeong Kim , Dogyoon Lee , Suhwan Cho , Minhyeok Lee , Wonjoon Lee , Taeoh Kim , Dongyoon Wee , Sangyoun Lee

During the Gaussian Splatting optimization process, the scene's geometry can gradually deteriorate if its structure is not deliberately preserved, especially in non-textured regions such as walls, ceilings, and furniture surfaces. This…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yanyan Li , Chenyu Lyu , Yan Di , Guangyao Zhai , Gim Hee Lee , Federico Tombari

We introduce PhysGaussian, a new method that seamlessly integrates physically grounded Newtonian dynamics within 3D Gaussians to achieve high-quality novel motion synthesis. Employing a custom Material Point Method (MPM), our approach…

Graphics · Computer Science 2024-04-16 Tianyi Xie , Zeshun Zong , Yuxing Qiu , Xuan Li , Yutao Feng , Yin Yang , Chenfanfu Jiang

Given a single image of a target object, image-to-3D generation aims to reconstruct its texture and geometric shape. Recent methods often utilize intermediate media, such as multi-view images or videos, to bridge the gap between input image…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Jiacheng Wang , Zhedong Zheng , Wei Xu , Ping Liu

To achieve realistic immersion in landscape images, fluids such as water and clouds need to move within the image while revealing new scenes from various camera perspectives. Recently, a field called dynamic scene video has emerged, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 In-Hwan Jin , Haesoo Choo , Seong-Hun Jeong , Heemoon Park , Junghwan Kim , Oh-joon Kwon , Kyeongbo Kong