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Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern real-world dynamics. However, evaluating whether generated videos actually follow these…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Juyi Lin , Arash Akbari , Yumei He , Lin Zhao , Haichao Zhang , Arman Akbari , Xingchen Xu , Zoe Y. Lu , Enfu Nan , Hokin Deng , Edmund Yeh , Sarah Ostadabbas , Yun Fu , Jennifer Dy , Pu Zhao , Yanzhi Wang

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

Developing embodied AI agents requires scalable training environments that balance content diversity with physics accuracy. World simulators provide such environments but face distinct limitations: video-based methods generate diverse…

The scarcity of large-scale robotic data has motivated the repurposing of foundation models from other modalities for policy learning. In this work, we introduce PhysGen (Learning Physics from Pretrained Video Generation Models), a scalable…

Robotics · Computer Science 2026-04-24 Zijian Song , Qichang Li , Sihan Qin , Yuhao Chen , Tianshui Chen , Liang Lin , Guangrun Wang

Automatically generating high-quality real world 3D scenes is of enormous interest for applications such as virtual reality and robotics simulation. Towards this goal, we introduce NeuralField-LDM, a generative model capable of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Seung Wook Kim , Bradley Brown , Kangxue Yin , Karsten Kreis , Katja Schwarz , Daiqing Li , Robin Rombach , Antonio Torralba , Sanja Fidler

Generating high-quality 3D objects from textual descriptions remains a challenging problem due to computational cost, the scarcity of 3D data, and complex 3D representations. We introduce Geometry Image Diffusion (GIMDiffusion), a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Slava Elizarov , Ciara Rowles , Simon Donné

This document is a hands-on, comprehensive guide to deep learning in the realm of physical simulations. Rather than just theory, we emphasize practical application: every concept is paired with interactive Jupyter notebooks to get you up…

Machine Learning · Computer Science 2025-03-28 N. Thuerey , B. Holzschuh , P. Holl , G. Kohl , M. Lino , Q. Liu , P. Schnell , F. Trost

High-fidelity haptic feedback is essential for immersive virtual environments, yet authoring realistic tactile textures remains a significant bottleneck for designers. We introduce HapticMatch, a visual-to-tactile generation framework…

Human-Computer Interaction · Computer Science 2026-01-26 Mingxin Zhang , Yu Yao , Yasutoshi Makino , Hiroyuki Shinoda , Masashi Sugiyama

Talking head generation creates lifelike avatars from static portraits for virtual communication and content creation. However, current models do not yet convey the feeling of truly interactive communication, often generating one-way…

Machine Learning · Computer Science 2026-01-05 Taekyung Ki , Sangwon Jang , Jaehyeong Jo , Jaehong Yoon , Sung Ju Hwang

Recent approaches have demonstrated the promise of using diffusion models to generate interactive and explorable worlds. However, most of these methods face critical challenges such as excessively large parameter sizes, reliance on lengthy…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xiaofeng Mao , Zhen Li , Chuanhao Li , Xiaojie Xu , Kaining Ying , Tong He , Jiangmiao Pang , Yu Qiao , Kaipeng Zhang

Synthesizing interactive 3D scenes from text is essential for gaming, virtual reality, and embodied AI. However, existing methods face several challenges. Learning-based approaches depend on small-scale indoor datasets, limiting the scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Lu Ling , Chen-Hsuan Lin , Tsung-Yi Lin , Yifan Ding , Yu Zeng , Yichen Sheng , Yunhao Ge , Ming-Yu Liu , Aniket Bera , Zhaoshuo Li

Recent diffusion-based text-to-image customization methods have achieved significant success in understanding concrete concepts to control generation processes, such as styles and shapes. However, few efforts dive into the realistic yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Fan Wu , Cheng Chen , Zhoujie Fu , Jiacheng Wei , Yi Xu , Deheng Ye , Guosheng Lin

We propose a novel task of text-controlled human object interaction generation in 3D scenes with movable objects. Existing human-scene interaction datasets suffer from insufficient interaction categories and typically only consider…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Xinhao Cai , Minghang Zheng , Xin Jin , Yang Liu

We introduce PhysWorld, a framework that enables robot learning from video generation through physical world modeling. Recent video generation models can synthesize photorealistic visual demonstrations from language commands and images,…

Physically-based rendering (PBR) has become a cornerstone in modern computer graphics, enabling realistic material representation and lighting interactions in 3D scenes. In this paper, we present MaterialMVP, a novel end-to-end model for…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Zebin He , Mingxin Yang , Shuhui Yang , Yixuan Tang , Tao Wang , Kaihao Zhang , Guanying Chen , Yuhong Liu , Jie Jiang , Chunchao Guo , Wenhan Luo

Interactive 3D simulated objects are crucial in AR/VR, animations, and robotics, driving immersive experiences and advanced automation. However, creating these articulated objects requires extensive human effort and expertise, limiting…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Long Le , Jason Xie , William Liang , Hung-Ju Wang , Yue Yang , Yecheng Jason Ma , Kyle Vedder , Arjun Krishna , Dinesh Jayaraman , Eric Eaton

Fieldwork still is the first and foremost source of insight in many disciplines of the geosciences. Virtual fieldwork is an approach meant to enable scientists trained in fieldwork to apply these skills to a virtual representation of…

Human-Computer Interaction · Computer Science 2025-01-16 Armin Bernstetter , Tom Kwasnitschka , Jens Karstens , Markus Schlüter , Isabella Peters

Physics-based simulation of mesh based domains remains a challenging task. State-of-the-art techniques can produce realistic results but require expert knowledge. A major bottleneck in many approaches is the step of integrating a potential…

Graphics · Computer Science 2023-11-07 Oshri Halimi , Egor Larionov , Zohar Barzelay , Philipp Herholz , Tuur Stuyck

Generative video models achieve high visual fidelity but often violate basic physical principles, limiting reliability in real-world settings. Prior attempts to inject physics rely on conditioning: frame-level signals are domain-specific…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Saurabh Pathak , Elahe Arani , Mykola Pechenizkiy , Bahram Zonooz

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