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In recent years, there has been rapid development in 3D generation models, opening up new possibilities for applications such as simulating the dynamic movements of 3D objects and customizing their behaviors. However, current 3D generative…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Fangfu Liu , Hanyang Wang , Shunyu Yao , Shengjun Zhang , Jie Zhou , Yueqi Duan

Accurately simulating existing 3D objects and a wide variety of materials often demands expert knowledge and time-consuming physical parameter tuning to achieve the desired dynamic behavior. We introduce MotionPhysics, an end-to-end…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Miaowei Wang , Jakub Zadrożny , Oisin Mac Aodha , Amir Vaxman

Realistic simulation of dynamic scenes requires accurately capturing diverse material properties and modeling complex object interactions grounded in physical principles. However, existing methods are constrained to basic material types…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Zhuoman Liu , Weicai Ye , Yan Luximon , Pengfei Wan , Di Zhang

Recent advances in video diffusion models have enabled the generation of high-quality videos. However, these videos still suffer from unrealistic deformations, semantic violations, and physical inconsistencies that are largely rooted in the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Shurui Gui , Deep Anil Patel , Xiner Li , Martin Renqiang Min

Animating a still image offers an engaging visual experience. Traditional image animation techniques mainly focus on animating natural scenes with stochastic dynamics (e.g. clouds and fluid) or domain-specific motions (e.g. human hair or…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Jinbo Xing , Menghan Xia , Yong Zhang , Haoxin Chen , Wangbo Yu , Hanyuan Liu , Xintao Wang , Tien-Tsin Wong , Ying Shan

Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take advantage of various off-the-shelf 3D assets with multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yanqin Jiang , Chaohui Yu , Chenjie Cao , Fan Wang , Weiming Hu , Jin Gao

We present a novel video generation framework that integrates 3-dimensional geometry and dynamic awareness. To achieve this, we augment 2D videos with 3D point trajectories and align them in pixel space. The resulting 3D-aware video…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Yunuo Chen , Junli Cao , Vidit Goel , Sergei Korolev , Chenfanfu Jiang , Jian Ren , Sergey Tulyakov , Anil Kag

Modeling sounds emitted from physical object interactions is critical for immersive perceptual experiences in real and virtual worlds. Traditional methods of impact sound synthesis use physics simulation to obtain a set of physics…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Kun Su , Kaizhi Qian , Eli Shlizerman , Antonio Torralba , Chuang Gan

Recent video diffusion models have demonstrated their great capability in generating visually-pleasing results, while synthesizing the correct physical effects in generated videos remains challenging. The complexity of real-world motions,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Ke Zhang , Cihan Xiao , Jiacong Xu , Yiqun Mei , Vishal M. Patel

Image diffusion distillation achieves high-fidelity generation with very few sampling steps. However, applying these techniques directly to video diffusion often results in unsatisfactory frame quality due to the limited visual quality in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Yuanhao Zhai , Kevin Lin , Zhengyuan Yang , Linjie Li , Jianfeng Wang , Chung-Ching Lin , David Doermann , Junsong Yuan , Lijuan Wang

Recent video diffusion models have achieved impressive capabilities as large-scale generative world models. However, these models often struggle with fine-grained physical consistency, exhibiting physically implausible dynamics over time.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Haoran Lu , Shang Wu , Jianshu Zhang , Maojiang Su , Guo Ye , Chenwei Xu , Lie Lu , Pranav Maneriker , Fan Du , Manling Li , Zhaoran Wang , Han Liu

Generative models, particularly diffusion models, have made significant success in data synthesis across various modalities, including images, videos, and 3D assets. However, current diffusion models are computationally intensive, often…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Yuanzhi Zhu , Hanshu Yan , Huan Yang , Kai Zhang , Junnan Li

3D Gaussian Splatting has recently enabled fast and photorealistic reconstruction of static 3D scenes. However, dynamic editing of such scenes remains a significant challenge. We introduce a novel framework, Physics-Guided Score…

Graphics · Computer Science 2026-03-26 Gal Fiebelman , Hadar Averbuch-Elor , Sagie Benaim

Given a visual scene, humans have strong intuitions about how a scene can evolve over time under given actions. The intuition, often termed visual intuitive physics, is a critical ability that allows us to make effective plans to manipulate…

Computer Vision and Pattern Recognition · Computer Science 2023-04-25 Haotian Xue , Antonio Torralba , Joshua B. Tenenbaum , Daniel LK Yamins , Yunzhu Li , Hsiao-Yu Tung

We tackle the problem of text-driven 3D generation from a geometry alignment perspective. Given a set of text prompts, we aim to generate a collection of objects with semantically corresponding parts aligned across them. Recent methods…

While 3D hand reconstruction from monocular images has made significant progress, generating accurate and temporally coherent motion estimates from videos remains challenging, particularly during hand-object interactions. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Yufei Zhang , Zijun Cui , Jeffrey O. Kephart , Qiang Ji

We introduce latent intuitive physics, a transfer learning framework for physics simulation that can infer hidden properties of fluids from a single 3D video and simulate the observed fluid in novel scenes. Our key insight is to use latent…

Artificial Intelligence · Computer Science 2024-08-06 Xiangming Zhu , Huayu Deng , Haochen Yuan , Yunbo Wang , Xiaokang Yang

Animation techniques bring digital 3D worlds and characters to life. However, manual animation is tedious and automated techniques are often specialized to narrow shape classes. In our work, we propose a technique for automatic re-animation…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Lukas Uzolas , Elmar Eisemann , Petr Kellnhofer

We introduce PhysMotion, a novel framework that leverages principled physics-based simulations to guide intermediate 3D representations generated from a single image and input conditions (e.g., applied force and torque), producing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Xiyang Tan , Ying Jiang , Xuan Li , Zeshun Zong , Tianyi Xie , Yin Yang , Chenfanfu Jiang

Animatable 3D reconstruction has significant applications across various fields, primarily relying on artists' handcraft creation. Recently, some studies have successfully constructed animatable 3D models from monocular videos. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Tingyang Zhang , Qingzhe Gao , Weiyu Li , Libin Liu , Baoquan Chen
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