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Related papers: CAGE: Controllable Articulation GEneration

200 papers

We propose novel motion representations for animating articulated objects consisting of distinct parts. In a completely unsupervised manner, our method identifies object parts, tracks them in a driving video, and infers their motions by…

Computer Vision and Pattern Recognition · Computer Science 2021-04-26 Aliaksandr Siarohin , Oliver J. Woodford , Jian Ren , Menglei Chai , Sergey Tulyakov

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

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

The ability to generate diverse 3D articulated head avatars is vital to a plethora of applications, including augmented reality, cinematography, and education. Recent work on text-guided 3D object generation has shown great promise in…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Alexander W. Bergman , Wang Yifan , Gordon Wetzstein

Robots deployed in human-centric environments may need to manipulate a diverse range of articulated objects, such as doors, dishwashers, and cabinets. Articulated objects often come with unexpected articulation mechanisms that are…

Robotics · Computer Science 2023-01-19 Nick Heppert , Toki Migimatsu , Brent Yi , Claire Chen , Jeannette Bohg

Large-scale articulated objects with high quality are desperately needed for multiple tasks related to embodied AI. Most existing methods for creating articulated objects are either data-driven or simulation based, which are limited by the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Xinyu Lian , Zichao Yu , Ruiming Liang , Yitong Wang , Li Ray Luo , Kaixu Chen , Yuanzhen Zhou , Qihong Tang , Xudong Xu , Zhaoyang Lyu , Bo Dai , Jiangmiao Pang

In this work, we introduce a novel approach for creating controllable dynamics in 3D-generated Gaussians using casually captured reference videos. Our method transfers the motion of objects from reference videos to a variety of generated 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Zhoujie Fu , Jiacheng Wei , Wenhao Shen , Chaoyue Song , Xiaofeng Yang , Fayao Liu , Xulei Yang , Guosheng Lin

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

While recent advancements have shown remarkable progress in general 3D shape generation models, the challenge of leveraging these approaches to automatically generate wearable 3D assets remains unexplored. To this end, we present BAG, a…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Zhongjin Luo , Yang Li , Mingrui Zhang , Senbo Wang , Han Yan , Xibin Song , Taizhang Shang , Wei Mao , Hongdong Li , Xiaoguang Han , Pan Ji

Simulation is essential for autonomous driving, yet current frameworks often model vehicles as rigid assets and fail to capture part-level articulation. With perception algorithms increasingly leveraging dynamics such as wheel steering or…

Artificial Intelligence · Computer Science 2026-04-08 Shiyao Qian , Yuan Ren , Dongfeng Bai , Bingbing Liu

Most existing 3D assembly methods treat the problem as pure pose estimation, rearranging observed parts via rigid transformations. In contrast, human assembly naturally couples structural reasoning with holistic shape inference. Inspired by…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Zeyu Jiang , Sihang Li , Siqi Tan , Chenyang Xu , Juexiao Zhang , Julia Galway-Witham , Xue Wang , Scott A. Williams , Radu Iovita , Chen Feng , Jing Zhang

We explore a novel method to perceive and manipulate 3D articulated objects that generalizes to enable a robot to articulate unseen classes of objects. We propose a vision-based system that learns to predict the potential motions of the…

Robotics · Computer Science 2024-05-03 Ben Eisner , Harry Zhang , David Held

Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional objects from single images--particularly under occlusions--remains challenging. Existing methods often…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Hui Shan , Keyang Luo , Ming Li , Sizhe Zheng , Yanwei Fu , Zhen Chen , Xiangru Huang

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 ATOP (Articulate That Object Part), a novel few-shot method based on motion personalization to articulate a static 3D object with respect to a part and its motion as prescribed in a text prompt. Given the scarcity of available…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Aditya Vora , Sauradip Nag , Kai Wang , Hao Zhang

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

This paper considers the problem of modeling articulated objects captured in 2D videos to enable novel view synthesis, while also being easily editable, drivable, and re-posable. To tackle this challenging problem, we propose RigGS, a new…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Yuxin Yao , Zhi Deng , Junhui Hou

Controllable layout generation refers to the process of creating a plausible visual arrangement of elements within a graphic design (e.g., document and web designs) with constraints representing design intentions. Although recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Jian Chen , Ruiyi Zhang , Yufan Zhou , Rajiv Jain , Zhiqiang Xu , Ryan Rossi , Changyou Chen

As 3D Gaussian Splatting (3DGS) gains popularity as a 3D representation of real scenes, enabling user-friendly deformation to create novel scenes while preserving fine details from the original 3DGS has attracted significant research…

Graphics · Computer Science 2025-04-18 Yifei Tong , Runze Tian , Xiao Han , Dingyao Liu , Fenggen Yu , Yan Zhang

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