English
Related papers

Related papers: URDF-Anything+: Autoregressive Articulated 3D Mode…

200 papers

Constructing accurate digital twins of articulated objects is essential for robotic simulation training and embodied AI world model building, yet historically requires painstaking manual modeling or multi-stage pipelines. In this work, we…

Robotics · Computer Science 2025-11-04 Zhe Li , Xiang Bai , Jieyu Zhang , Zhuangzhe Wu , Che Xu , Ying Li , Chengkai Hou , Shanghang Zhang

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

This paper presents a novel framework for modeling and conditional generation of 3D articulated objects. Troubled by flexibility-quality tradeoffs, existing methods are often limited to using predefined structures or retrieving shapes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Jiayi Su , Youhe Feng , Zheng Li , Jinhua Song , Yangfan He , Botao Ren , Botian Xu

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

Articulated objects, as prevalent entities in human life, their 3D representations play crucial roles across various applications. However, achieving both high-fidelity textured surface reconstruction and dynamic generation for articulated…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Di Wu , Liu Liu , Zhou Linli , Anran Huang , Liangtu Song , Qiaojun Yu , Qi Wu , Cewu Lu

We tackle the challenge of concurrent reconstruction at the part level with the RGB appearance and estimation of motion parameters for building digital twins of articulated objects using the 3D Gaussian Splatting (3D-GS) method. With two…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Junfu Guo , Yu Xin , Gaoyi Liu , Kai Xu , Ligang Liu , Ruizhen Hu

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

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

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

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

We build rearticulable models for arbitrary everyday man-made objects containing an arbitrary number of parts that are connected together in arbitrary ways via 1 degree-of-freedom joints. Given point cloud videos of such everyday objects,…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Shaowei Liu , Saurabh Gupta , Shenlong Wang

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

Generating articulated assets is crucial for robotics, digital twins, and embodied intelligence. Existing generative models often rely on single-view inputs representing closed states, resulting in ambiguous or unrealistic kinematic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Haowen Wang , Xiaoping Yuan , Fugang Zhang , Rui Jian , Yuanwei Zhu , Xiuquan Qiao , Yakun Huang

Recent work has made significant progress on using implicit functions, as a continuous representation for 3D rigid object shape reconstruction. However, much less effort has been devoted to modeling general articulated objects. Compared to…

Computer Vision and Pattern Recognition · Computer Science 2021-04-16 Jiteng Mu , Weichao Qiu , Adam Kortylewski , Alan Yuille , Nuno Vasconcelos , Xiaolong Wang

We present Real2Code, a novel approach to reconstructing articulated objects via code generation. Given visual observations of an object, we first reconstruct its part geometry using an image segmentation model and a shape completion model.…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Zhao Mandi , Yijia Weng , Dominik Bauer , Shuran Song

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

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

Although commercial and open-source software exist to reconstruct a static object from a sequence recorded with an RGB-D sensor, there is a lack of tools that build rigged models of articulated objects that deform realistically and can be…

Computer Vision and Pattern Recognition · Computer Science 2016-09-12 Dimitrios Tzionas , Juergen Gall

We address the challenge of creating 3D assets for household articulated objects from a single image. Prior work on articulated object creation either requires multi-view multi-state input, or only allows coarse control over the generation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Jiayi Liu , Denys Iliash , Angel X. Chang , Manolis Savva , Ali Mahdavi-Amiri
‹ Prev 1 2 3 10 Next ›