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Realistic object interactions are crucial for creating immersive virtual experiences, yet synthesizing realistic 3D object dynamics in response to novel interactions remains a significant challenge. Unlike unconditional or text-conditioned…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Tianyuan Zhang , Hong-Xing Yu , Rundi Wu , Brandon Y. Feng , Changxi Zheng , Noah Snavely , Jiajun Wu , William T. Freeman

Recent advances in 3D content generation have amplified demand for dynamic models that are both visually realistic and physically consistent. However, state-of-the-art video diffusion models frequently produce implausible results such as…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Siwei Meng , Yawei Luo , Ping Liu

Video Diffusion Models (VDMs) offer a promising approach for simulating dynamic scenes and environments, with broad applications in robotics and media generation. However, existing models often generate temporally incoherent content that…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Zhexiao Xiong , Yizhi Song , Liu He , Wei Xiong , Yu Yuan , Feng Qiao , Nathan Jacobs

Modern video diffusion models excel at appearance synthesis but still struggle with physical consistency: objects drift, collisions lack realistic rebound, and material responses seldom match their underlying properties. We present PhyCo, a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Sriram Narayanan , Ziyu Jiang , Srinivasa Narasimhan , Manmohan Chandraker

Video Large Language Models (Video LLMs) have shown impressive performance across a wide range of video-language tasks. However, they often fail in scenarios requiring a deeper understanding of physical dynamics. This limitation primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Yu-Wei Zhan , Xin Wang , Hong Chen , Tongtong Feng , Wei Feng , Ren Wang , Guangyao Li , Qing Li , Wenwu Zhu

Achieving real-time physics-based animation that generalizes across diverse 3D shapes and discretizations remains a fundamental challenge. We introduce PhysSkin, a physics-informed framework that addresses this challenge. In the spirit of…

We present PhysGen, a novel image-to-video generation method that converts a single image and an input condition (e.g., force and torque applied to an object in the image) to produce a realistic, physically plausible, and temporally…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shaowei Liu , Zhongzheng Ren , Saurabh Gupta , Shenlong Wang

Realistic visual simulations are omnipresent, yet their creation requires computing time, rendering, and expert animation knowledge. Open-vocabulary visual effects generation from text inputs emerges as a promising solution that can unlock…

Graphics · Computer Science 2026-01-01 Luca Collorone , Mert Kiray , Indro Spinelli , Fabio Galasso , Benjamin Busam

With recent developments in Embodied Artificial Intelligence (EAI) research, there has been a growing demand for high-quality, large-scale interactive scene generation. While prior methods in scene synthesis have prioritized the naturalness…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Yandan Yang , Baoxiong Jia , Peiyuan Zhi , Siyuan Huang

Existing video generation models excel at producing photo-realistic videos from text or images, but often lack physical plausibility and 3D controllability. To overcome these limitations, we introduce PhysCtrl, a novel framework for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Chen Wang , Chuhao Chen , Yiming Huang , Zhiyang Dou , Yuan Liu , Jiatao Gu , Lingjie Liu

Traditional animation production decomposes visual elements into discrete layers to enable independent processing for sketching, refining, coloring, and in-betweening. Existing anime generation video methods typically treat animation as a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yuxue Yang , Lue Fan , Zuzeng Lin , Feng Wang , Zhaoxiang Zhang

Video generation models nowadays are capable of generating visually realistic videos, but often fail to adhere to physical laws, limiting their ability to generate physically plausible videos and serve as ''world models''. To address this…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Sihui Ji , Xi Chen , Xin Tao , Pengfei Wan , Hengshuang Zhao

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

Transforming static images into interactive experiences remains a challenging task in computer vision. Tackling this challenge holds the potential to elevate mobile user experiences, notably through interactive and AR/VR applications.…

While recent video generation models have achieved significant visual fidelity, they often suffer from the lack of explicit physical controllability and plausibility. To address this, some recent studies attempted to guide the video…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Haoze Zhang , Tianyu Huang , Zichen Wan , Xiaowei Jin , Hongzhi Zhang , Hui Li , Wangmeng Zuo

Creating hand-drawn animation sequences is labor-intensive and demands professional expertise. We introduce PhysAnimator, a novel approach for generating physically plausible meanwhile anime-stylized animation from static anime…

Graphics · Computer Science 2025-03-27 Tianyi Xie , Yiwei Zhao , Ying Jiang , Chenfanfu Jiang

Realistic digital avatars require expressive and dynamic hair motion; however, most existing head avatar methods assume rigid hair movement. These methods often fail to disentangle hair from the head, representing it as a simple outer shell…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Berna Kabadayi , Vanessa Sklyarova , Wojciech Zielonka , Justus Thies , Gerard Pons-Moll

Existing single-image 3D indoor scene generators often produce results that look visually plausible but fail to obey real-world physics, limiting their reliability in robotics, embodied AI, and design. To examine this gap, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Dongli Wu , Jingyu Hu , Ka-Hei Hui , Xiaobao Wei , Chengwen Luo , Jianqiang Li , Zhengzhe Liu

Understanding the physical world is a fundamental challenge in embodied AI, critical for enabling agents to perform complex tasks and operate safely in real-world environments. While Vision-Language Models (VLMs) have shown great promise in…

Computer Vision and Pattern Recognition · Computer Science 2025-01-30 Wei Chow , Jiageng Mao , Boyi Li , Daniel Seita , Vitor Guizilini , Yue Wang

Video diffusion models (VDMs) have advanced significantly in recent years, enabling the generation of highly realistic videos and drawing the attention of the community in their potential as world simulators. However, despite their…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Xindi Yang , Baolu Li , Yiming Zhang , Zhenfei Yin , Lei Bai , Liqian Ma , Zhiyong Wang , Jianfei Cai , Tien-Tsin Wong , Huchuan Lu , Xu Jia
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