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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

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

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

3D modeling of articulated objects is a research problem within computer vision, graphics, and robotics. Its objective is to understand the shape and motion of the articulated components, represent the geometry and mobility of object parts,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Jiayi Liu , Manolis Savva , Ali Mahdavi-Amiri

A deep understanding of kinematic structures and movable components is essential for enabling robots to manipulate objects and model their own articulated forms. Such understanding is captured through articulated objects, which are…

Robotics · Computer Science 2026-03-04 Jiawei Wang , Dingyou Wang , Jiaming Hu , Qixuan Zhang , Jingyi Yu , Lan Xu

Articulated object manipulation remains a critical challenge in robotics due to the complex kinematic constraints and the limited physical reasoning of existing methods. In this work, we introduce ArtGS, a novel framework that extends 3D…

Robotics · Computer Science 2025-07-04 Qiaojun Yu , Xibin Yuan , Yu jiang , Junting Chen , Dongzhe Zheng , Ce Hao , Yang You , Yixing Chen , Yao Mu , Liu Liu , Cewu Lu

We present ArtMesh, a mesh-native method for reconstructing articulated objects explicitly as connected triangle meshes with per-part rigid motion from multi-view images in start and end states. Existing 3D Gaussian Splatting pipelines for…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Sylvia Yuan , Dan Wang , Ravi Ramamoorthi , Xinrui Cui

Articulated object manipulation is a critical capability for robots to perform various tasks in real-world scenarios. Composed of multiple parts connected by joints, articulated objects are endowed with diverse functional mechanisms through…

Robotics · Computer Science 2025-02-18 Yuanfei Wang , Xiaojie Zhang , Ruihai Wu , Yu Li , Yan Shen , Mingdong Wu , Zhaofeng He , Yizhou Wang , Hao Dong

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

Articulated objects (e.g., doors and drawers) exist everywhere in our life. Different from rigid objects, articulated objects have higher degrees of freedom and are rich in geometries, semantics, and part functions. Modeling different kinds…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Yushi Du , Ruihai Wu , Yan Shen , Hao Dong

Articulated objects pose diverse manipulation challenges for robots. Since their internal structures are not directly observable, robots must adaptively explore and refine actions to generate successful manipulation trajectories. While…

Robotics · Computer Science 2025-07-25 Xiaojie Zhang , Yuanfei Wang , Ruihai Wu , Kunqi Xu , Yu Li , Liuyu Xiang , Hao Dong , Zhaofeng He

We introduce Particulate, a feed-forward model that, given a 3D mesh of an object, infers its articulations, including its 3D parts, their kinematic structure, and the motion constraints. The model is based on a transformer network, the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Ruining Li , Yuxin Yao , Chuanxia Zheng , Christian Rupprecht , Joan Lasenby , Shangzhe Wu , Andrea Vedaldi

The acquisition of substantial volumes of 3D articulated object data is expensive and time-consuming, and consequently the scarcity of 3D articulated object data becomes an obstacle for deep learning methods to achieve remarkable…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Jianhua Sun , Yuxuan Li , Jiude Wei , Longfei Xu , Nange Wang , Yining Zhang , Cewu Lu

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

Generalizable articulated object manipulation is essential for home-assistant robots. Recent efforts focus on imitation learning from demonstrations or reinforcement learning in simulation, however, due to the prohibitive costs of…

Robotics · Computer Science 2024-02-22 Wenke Xia , Dong Wang , Xincheng Pang , Zhigang Wang , Bin Zhao , Di Hu , Xuelong Li

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

Building interactive simulators and scalable robot-learning environments requires a large number of articulated assets. However, most existing 3D assets in simulation are rigid, and manually converting them into articulated objects is…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yixuan Yang , Luyang Xie , Zhen Luo , Zixiang Zhao , Tongsheng Ding , Mingqi Gao , Feng Zheng

We propose a training-free method, Articulate3D, to pose a 3D asset through language control. Despite advances in vision and language models, this task remains surprisingly challenging. To achieve this goal, we decompose the problem into…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Oishi Deb , Anjun Hu , Ashkan Khakzar , Philip Torr , Christian Rupprecht

With the explosive growth of 3D content creation, there is an increasing demand for automatically converting static 3D models into articulation-ready versions that support realistic animation. Traditional approaches rely heavily on manual…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Chaoyue Song , Jianfeng Zhang , Xiu Li , Fan Yang , Yiwen Chen , Zhongcong Xu , Jun Hao Liew , Xiaoyang Guo , Fayao Liu , Jiashi Feng , Guosheng Lin

Building articulated objects is a key challenge in computer vision. Existing methods often fail to effectively integrate information across different object states, limiting the accuracy of part-mesh reconstruction and part dynamics…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Yu Liu , Baoxiong Jia , Ruijie Lu , Junfeng Ni , Song-Chun Zhu , Siyuan Huang
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