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Creating interactive digital environments for gaming, robotics, and simulation relies on articulated 3D objects whose functionality emerges from their part geometry and kinematic structure. However, existing approaches remain fundamentally…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Penghao Wang , Siyuan Xie , Hongyu Yan , Xianghui Yang , Jingwei Huang , Chunchao Guo , Jiayuan Gu

Articulated 3D objects play a vital role in realistic simulation and embodied robotics, yet manually constructing such assets remains costly and difficult to scale. In this paper, we present UniArt, a diffusion-based framework that directly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Bu Jin , Weize Li , Songen Gu , Yupeng Zheng , Yuhang Zheng , Zhengyi Zhou , Yao Yao

Generating articulated objects, such as laptops and microwaves, is a crucial yet challenging task with extensive applications in Embodied AI and AR/VR. Current image-to-3D methods primarily focus on surface geometry and texture, neglecting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Ruijie Lu , Yu Liu , Jiaxiang Tang , Junfeng Ni , Yuxiang Wang , Diwen Wan , Gang Zeng , Yixin Chen , Siyuan Huang

Articulated 3D objects are critical for embodied AI, robotics, and interactive scene understanding, yet creating simulation-ready assets remains labor-intensive and requires expert modeling of part hierarchies and motion structures. We…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Yumeng He , Ying Jiang , Jiayin Lu , Yin Yang , Chenfanfu Jiang

Understanding articulated objects from monocular video is a crucial yet challenging task in robotics and digital twin creation. Existing methods often rely on complex multi-view setups, high-fidelity object scans, or fragile long-term point…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Arslan Artykov , Tom Ravaud , Corentin Sautier , Vincent Lepetit

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

Articulated 3D object generation is fundamental for creating realistic, functional, and interactable virtual assets which are not simply static. We introduce MeshArt, a hierarchical transformer-based approach to generate articulated 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Daoyi Gao , Yawar Siddiqui , Lei Li , Angela Dai

Converting static 3D meshes into interactable articulated assets is crucial for embodied AI and robotic simulation. However, existing zero-shot pipelines struggle with complex assets due to a critical lack of physical grounding.…

Robotics · Computer Science 2026-03-16 WenBo Xu , Liu Liu , Li Zhang , Dan Guo , RuoNan Liu

Articulated objects are central to interactive 3D applications, including embodied AI, robotics, and VR/AR, where functional part decomposition and kinematic motion are essential. Yet producing high-fidelity articulated assets remains…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Qingming Liu , Xinyue Yao , Shuyuan Zhang , Yueci Deng , Guiliang Liu , Zhen Liu , Kui Jia

Modeling 3D articulated objects with realistic geometry, textures, and kinematics is essential for a wide range of applications. However, existing optimization-based reconstruction methods often require dense multi-view inputs and expensive…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Sylvia Yuan , Ruoxi Shi , Xinyue Wei , Xiaoshuai Zhang , Hao Su , Minghua Liu

Reconstructing articulated 3D objects from a single image requires jointly inferring object geometry, part structure, and motion parameters from limited visual evidence. A key difficulty lies in the entanglement between motion cues and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Haitian Li , Haozhe Xie , Junxiang Xu , Beichen Wen , Fangzhou Hong , Ziwei Liu

We propose ArtiLatent, a generative framework that synthesizes human-made 3D objects with fine-grained geometry, accurate articulation, and realistic appearance. Our approach jointly models part geometry and articulation dynamics by…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Honghua Chen , Yushi Lan , Yongwei Chen , Xingang Pan

A bottleneck in learning to understand articulated 3D objects is the lack of large and diverse datasets. In this paper, we propose to leverage large language models (LLMs) to close this gap and generate articulated assets at scale. We…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Matt Zhou , Ruining Li , Xiaoyang Lyu , Zhaomou Song , Zhening Huang , Chuanxia Zheng , Christian Rupprecht , Andrea Vedaldi , Shangzhe Wu

Advances in 3D generative AI have enabled the creation of physical objects from text prompts, but challenges remain in creating objects involving multiple component types. We present a pipeline that integrates 3D generative AI with…

3D articulated objects modeling has long been a challenging problem, since it requires to capture both accurate surface geometries and semantically meaningful and spatially precise structures, parts, and joints. Existing methods heavily…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Xiaowen Qiu , Jincheng Yang , Yian Wang , Zhehuan Chen , Yufei Wang , Tsun-Hsuan Wang , Zhou Xian , Chuang Gan

Recent advancements in 3D generation models have opened new possibilities for simulating dynamic 3D object movements and customizing behaviors, yet creating this content remains challenging. Current methods often require manual assignment…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Haoyu Zhao , Hao Wang , Xingyue Zhao , Hao Fei , Hongqiu Wang , Chengjiang Long , Hua Zou

We introduce a novel 3D generation method for versatile and high-quality 3D asset creation. The cornerstone is a unified Structured LATent (SLAT) representation which allows decoding to different output formats, such as Radiance Fields, 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Jianfeng Xiang , Zelong Lv , Sicheng Xu , Yu Deng , Ruicheng Wang , Bowen Zhang , Dong Chen , Xin Tong , Jiaolong Yang

Articulated objects are commonly found in daily life. It is essential that robots can exhibit robust perception and manipulation skills for articulated objects in real-world robotic applications. However, existing methods for articulated…

Robotics · Computer Science 2024-10-01 Junbo Wang , Wenhai Liu , Qiaojun Yu , Yang You , Liu Liu , Weiming Wang , Cewu Lu

3D modeling is shifting from static visual representations toward physical, articulated assets that can be directly used in simulation and interaction. However, most existing 3D generation methods overlook key physical and articulation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Ziang Cao , Fangzhou Hong , Zhaoxi Chen , Liang Pan , Ziwei Liu

Reconstructing articulated objects is essential for building digital twins of interactive environments. However, prior methods typically decouple geometry and motion by first reconstructing object shape in distinct states and then…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Licheng Shen , Saining Zhang , Honghan Li , Peilin Yang , Zihao Huang , Zongzheng Zhang , Hao Zhao
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