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Related papers: PhyMix: Towards Physically Consistent Single-Image…

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Recent generative video models achieve impressive visual quality but remain constrained by limited physical consistency and controllability. Existing video generation methods provide minimal physical control, and single-image-to-3D…

Graphics · Computer Science 2026-05-21 Xin Zhang , Yabo Chen , Yijie Fang , Wanying Qu , Haibin Huang , Chi Zhang , Feng Xu , Xuelong Li

Reconstructing metrically accurate humans and their surrounding scenes from a single image is crucial for virtual reality, robotics, and comprehensive 3D scene understanding. However, existing methods struggle with depth ambiguity,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Pradyumna Yalandur Muralidhar , Yuxuan Xue , Xianghui Xie , Margaret Kostyrko , Gerard Pons-Moll

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

Despite recent advances in text-conditioned 3D indoor scene generation, there remain gaps in the evaluation of these methods. Existing metrics often measure realism by comparing generated scenes to a set of ground-truth scenes, but they…

Graphics · Computer Science 2026-03-10 Hou In Ivan Tam , Hou In Derek Pun , Austin T. Wang , Angel X. Chang , Manolis Savva

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

Existing image-to-video generation methods often produce physically implausible motions and lack precise control over object dynamics. While prior approaches have incorporated physics simulators, they remain confined to 2D planar motions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Tianyidan Xie , Zhentao Huang , Mingjie Wang , Xin Huang , Jun Zhou , Minglun Gong , Zili Yi

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

Recent advances in 3D scene generation produce visually appealing output, but current representations hinder artists' workflows that require modifiable 3D textured mesh scenes for visual effects and game development. Despite significant…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Tobias Sautter , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

In recent years, 3D generation has made great strides in both academia and industry. However, generating 3D scenes from a single RGB image remains a significant challenge, as current approaches often struggle to ensure both object…

Graphics · Computer Science 2026-02-18 Xiang Tang , Ruotong Li , Xiaopeng Fan

This paper presents a novel generative approach that outputs 3D indoor environments solely from a textual description of the scene. Current methods often treat scene synthesis as a mere layout prediction task, leading to rooms with…

Machine Learning · Computer Science 2025-02-12 Yao Wei , Matteo Toso , Pietro Morerio , Michael Ying Yang , Alessio Del Bue

Generating high-quality textures for 3D scenes is crucial for applications in interior design, gaming, and augmented/virtual reality (AR/VR). Although recent advancements in 3D generative models have enhanced content creation, significant…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Yunfan Zhang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicolas Vun

The techniques for 3D indoor scene capturing are widely used, but the meshes produced leave much to be desired. In this paper, we propose "RoomDreamer", which leverages powerful natural language to synthesize a new room with a different…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Liangchen Song , Liangliang Cao , Hongyu Xu , Kai Kang , Feng Tang , Junsong Yuan , Yang Zhao

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

Simulation has become a key tool for training and evaluating home robots at scale, yet existing environments fail to capture the diversity and physical complexity of real indoor spaces. Current scene synthesis methods produce sparsely…

Robotics · Computer Science 2026-02-12 Nicholas Pfaff , Thomas Cohn , Sergey Zakharov , Rick Cory , Russ Tedrake

Reconstructing physically stable 3D scenes from a single RGB image enables casual images to be converted into simulation-ready digital assets for applications such as immersive interaction and content creation. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Xiaoxuan Ma , Jiashun Wang , Nicolas Ugrinovic , Yehonathan Litman , Kris Kitani

Simulation-ready physical 3D assets have emerged as a promising direction owing to their broad applicability in downstream tasks. However, most existing 3D generation methods either neglect physical properties or are limited to a single…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Ziang Cao , Yinghao Liu , Haitian Li , Runmao Yao , Fangzhou Hong , Zhaoxi Chen , Liang Pan , Ziwei Liu

Existing generative models for 3D shapes can synthesize high-fidelity and visually plausible shapes. For certain classes of shapes that have undergone an engineering design process, the realism of the shape is tightly coupled with the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yingxuan You , Chen Zhao , Hantao Zhang , Ming Xu , Pascal Fua

Compositional 3D scene generation from a single view requires the simultaneous recovery of scene layout and 3D assets. Existing approaches mainly fall into two categories: feed-forward generation methods and per-instance generation methods.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Ze-Xin Yin , Liu Liu , Xinjie Wang , Wei Sui , Zhizhong Su , Jian Yang , Jin Xie

We propose SceneTex, a novel method for effectively generating high-quality and style-consistent textures for indoor scenes using depth-to-image diffusion priors. Unlike previous methods that either iteratively warp 2D views onto a mesh…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Dave Zhenyu Chen , Haoxuan Li , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

Physics-aware symbolic simulation of 3D scenes is critical for robotics, embodied AI, and scientific computing, requiring models to understand natural language descriptions of physical phenomena and translate them into executable simulation…

Robotics · Computer Science 2026-04-28 Tianyidan Xie , Peiyu Wang , Yuyi Qian , Yuxuan Wang , Rui Ma , Ying Tai , Song Wu , Qian Wang , Lanjun Wang , Zili Yi
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