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Related papers: PhysMotion: Physics-Grounded Dynamics From a Singl…

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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

We present a new test-time optimization method for estimating dense and long-range motion from a video sequence. Prior optical flow or particle video tracking algorithms typically operate within limited temporal windows, struggling to track…

Computer Vision and Pattern Recognition · Computer Science 2023-09-13 Qianqian Wang , Yen-Yu Chang , Ruojin Cai , Zhengqi Li , Bharath Hariharan , Aleksander Holynski , Noah Snavely

We present Pix2Gif, a motion-guided diffusion model for image-to-GIF (video) generation. We tackle this problem differently by formulating the task as an image translation problem steered by text and motion magnitude prompts, as shown in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-11 Hitesh Kandala , Jianfeng Gao , Jianwei Yang

Single-image 3D reconstruction remains a fundamental challenge in computer vision due to inherent geometric ambiguities and limited viewpoint information. Recent advances in Latent Video Diffusion Models (LVDMs) offer promising 3D priors…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Yabo Chen , Chen Yang , Jiemin Fang , Xiaopeng Zhang , Lingxi Xie , Wei Shen , Wenrui Dai , Hongkai Xiong , Qi Tian

In this paper, we propose Scene Splatter, a momentum-based paradigm for video diffusion to generate generic scenes from single image. Existing methods, which employ video generation models to synthesize novel views, suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Shengjun Zhang , Jinzhao Li , Xin Fei , Hao Liu , Yueqi Duan

Generating physically feasible dynamics in a data-driven context is challenging, especially when adhering to physical priors expressed in specific equations or formulas. Existing methodologies often overlook the integration of physical…

Machine Learning · Computer Science 2026-02-16 Zihan Zhou , Xiaoxue Wang , Tianshu Yu

We introduce a novel approach to reconstruct simulation-ready garments with intricate appearance. Despite recent advancements, existing methods often struggle to balance the need for accurate garment reconstruction with the ability to…

The advancement of 4D (i.e., sequential 3D) generation opens up new possibilities for lifelike experiences in various applications, where users can explore dynamic objects or characters from any viewpoint. Meanwhile, video generative models…

Graphics · Computer Science 2025-04-08 Yikai Wang , Guangce Liu , Xinzhou Wang , Zilong Chen , Jiafang Li , Xin Liang , Fuchun Sun , Jun Zhu

Realistic reconstruction of dynamic 4D scenes from monocular videos is essential for understanding the physical world. Despite recent progress in neural rendering, existing methods often struggle to recover accurate 3D geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Haoran Zhou , Gim Hee Lee

We address the task of generating physically accurate and visually faithful 4D Human-Object Interaction (HOI). Given a static 3D human and target object represented as 3D Gaussian Splats (3DGS), our goal is to synthesize dynamic scenes…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Omer Benishu , Gal Fiebelman , Sagie Benaim

Recent advances in deep generative modeling have unlocked unprecedented opportunities for video synthesis. In real-world applications, however, users often seek tools to faithfully realize their creative editing intentions with precise and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Yuhao Liu , Tengfei Wang , Fang Liu , Zhenwei Wang , Rynson W. H. Lau

Existing deep models predict 2D and 3D kinematic poses from video that are approximately accurate, but contain visible errors that violate physical constraints, such as feet penetrating the ground and bodies leaning at extreme angles. In…

Computer Vision and Pattern Recognition · Computer Science 2020-07-27 Davis Rempe , Leonidas J. Guibas , Aaron Hertzmann , Bryan Russell , Ruben Villegas , Jimei Yang

One image to editable dynamic 3D model and video generation is novel direction and change in the research area of single image to 3D representation or 3D reconstruction of image. Gaussian Splatting has demonstrated its advantages in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Jinwei Lin

Physics-based understanding of object interactions from sensory observations is an essential capability in augmented reality and robotics. It enables to capture the properties of a scene for simulation and control. In this paper, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Rama Krishna Kandukuri , Michael Strecke , Joerg Stueckler

We present StableMotion, a novel framework leverages knowledge (geometry and content priors) from pretrained large-scale image diffusion models to perform motion estimation, solving single-image-based image rectification tasks such as…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Ziyi Wang , Haipeng Li , Lin Sui , Tianhao Zhou , Hai Jiang , Lang Nie , Shuaicheng Liu

Recent advances in video generation have led to remarkable improvements in visual quality and temporal coherence. Upon this, trajectory-controllable video generation has emerged to enable precise object motion control through explicitly…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Quanhao Li , Zhen Xing , Rui Wang , Hui Zhang , Qi Dai , Zuxuan Wu

Structure-from-Motion -- the process of simultaneously estimating camera poses and 3D scene structure from a collection of images -- remains a central challenge in computer vision, with many open problems yet to be solved. Recent advances…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Linfei Pan , Johannes Schönberger , Marc Pollefeys

Text-guided human motion generation has drawn significant interest because of its impactful applications spanning animation and robotics. Recently, application of diffusion models for motion generation has enabled improvements in the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-17 Samaneh Azadi , Akbar Shah , Thomas Hayes , Devi Parikh , Sonal Gupta

We demonstrate the feasibility of integrating physics-based animations of solids and fluids with 3D Gaussian Splatting (3DGS) to create novel effects in virtual scenes reconstructed using 3DGS. Leveraging the coherence of the Gaussian…

We present a novel method for generating geometrically realistic and consistent orbital videos from a single image of an object. Existing video generation works mostly rely on pixel-wise attention to enforce view consistency across frames.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Rong Wang , Ruyi Zha , Ziang Cheng , Jiayu Yang , Pulak Purkait , Hongdong Li