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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

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

Articulated objects are essential for embodied AI and world models, yet inferring their kinematics from a single closed-state image remains challenging because crucial motion cues are often occluded. Existing methods either require…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Hang Zhang , Qijian Tian , Jingyu Gong , Daoguo Dong , Xuhong Wang , Yuan Xie , Xin Tan

The increasing demand for high-quality 3D content creation has motivated the development of automated methods for creating 3D object models from a single image and/or from a text prompt. However, the reconstructed 3D objects using…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Hoigi Seo , Hayeon Kim , Gwanghyun Kim , Se Young Chun

Synthesizing physically plausible articulated human-object interactions (HOI) without 3D/4D supervision remains a fundamental challenge. While recent zero-shot approaches leverage video diffusion models to synthesize human-object…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Zihao Huang , Tianqi Liu , Zhaoxi Chen , Shaocong Xu , Saining Zhang , Lixing Xiao , Zhiguo Cao , Wei Li , Hao Zhao , Ziwei Liu

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

Recently, the surge of efficient and automated 3D AI-generated content (AIGC) methods has increasingly illuminated the path of transforming human imagination into complex 3D structures. However, the automated generation of 3D content is…

Graphics · Computer Science 2024-12-20 Pei Chen , Fudong Wang , Yixuan Tong , Jingdong Chen , Ming Yang , Minghui Yang

Generative 3D modeling has advanced rapidly, driven by applications in VR/AR, metaverse, and robotics. However, most methods represent the target object as a closed mesh devoid of any structural information, limiting editing, animation, and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Omid Bonakdar , Nasser Mozayani

State-of-the-arts text-to-image generation models such as Imagen and Stable Diffusion Model have succeed remarkable progresses in synthesizing high-quality, feature-rich images with high resolution guided by human text prompts. Since…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Ziyi Dong , Pengxu Wei , Liang Lin

This work presents IAAO, a novel framework that builds an explicit 3D model for intelligent agents to gain understanding of articulated objects in their environment through interaction. Unlike prior methods that rely on task-specific…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Can Zhang , Gim Hee Lee

Generative models for 3D object synthesis have seen significant advancements with the incorporation of prior knowledge distilled from 2D diffusion models. Nevertheless, challenges persist in the form of multi-view geometric inconsistencies…

Computer Vision and Pattern Recognition · Computer Science 2023-11-20 Lincong Feng , Muyu Wang , Maoyu Wang , Kuo Xu , Xiaoli Liu

Manipulating unseen articulated objects through visual feedback is a critical but challenging task for real robots. Existing learning-based solutions mainly focus on visual affordance learning or other pre-trained visual models to guide…

Robotics · Computer Science 2024-04-29 Pengwei Xie , Rui Chen , Siang Chen , Yuzhe Qin , Fanbo Xiang , Tianyu Sun , Jing Xu , Guijin Wang , Hao Su

The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, limiting their utility. We introduce OmniPart, a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yunhan Yang , Yufan Zhou , Yuan-Chen Guo , Zi-Xin Zou , Yukun Huang , Ying-Tian Liu , Hao Xu , Ding Liang , Yan-Pei Cao , Xihui Liu

This paper presents a novel approach 4DRecons that takes a single camera RGB-D sequence of a dynamic subject as input and outputs a complete textured deforming 3D model over time. 4DRecons encodes the output as a 4D neural implicit surface…

Computer Vision and Pattern Recognition · Computer Science 2024-06-17 Xiaoyan Cong , Haitao Yang , Liyan Chen , Kaifeng Zhang , Li Yi , Chandrajit Bajaj , Qixing Huang

Recently, 3D Gaussian splatting (3D-GS) has achieved great success in reconstructing and rendering real-world scenes. To transfer the high rendering quality to generation tasks, a series of research works attempt to generate 3D-Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Taoran Yi , Jiemin Fang , Zanwei Zhou , Junjie Wang , Guanjun Wu , Lingxi Xie , Xiaopeng Zhang , Wenyu Liu , Xinggang Wang , Qi Tian

Recent advances in 3D generation have been remarkable, with methods such as DreamFusion leveraging large-scale text-to-image diffusion-based models to guide 3D object generation. These methods enable the synthesis of detailed and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Bohan Zeng , Shanglin Li , Yutang Feng , Ling Yang , Hong Li , Sicheng Gao , Jiaming Liu , Conghui He , Wentao Zhang , Jianzhuang Liu , Baochang Zhang , Shuicheng Yan

We present DreamAvatar, a text-and-shape guided framework for generating high-quality 3D human avatars with controllable poses. While encouraging results have been reported by recent methods on text-guided 3D common object generation,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

Given a single image of a general object such as a chair, could we also restore its articulated 3D shape similar to human modeling, so as to animate its plausible articulations and diverse motions? This is an interesting new question that…

Computer Vision and Pattern Recognition · Computer Science 2022-07-07 Ji Yang , Xinxin Zuo , Sen Wang , Zhenbo Yu , Xingyu Li , Bingbing Ni , Minglun Gong , Li Cheng

Dynamic Neural Radiance Fields (NeRFs) achieve remarkable visual quality when synthesizing novel views of time-evolving 3D scenes. However, the common reliance on backward deformation fields makes reanimation of the captured object poses…

Computer Vision and Pattern Recognition · Computer Science 2024-02-12 Lukas Uzolas , Elmar Eisemann , Petr Kellnhofer

The "one-shot" technique represents a distinct and sophisticated aesthetic in filmmaking. However, its practical realization is often hindered by prohibitive costs and complex real-world constraints. Although emerging video generation…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jiawei Liu , Junqiao Li , Jiangfan Deng , Gen Li , Siyu Zhou , Zetao Fang , Shanshan Lao , Zengde Deng , Jianing Zhu , Tingting Ma , Jiayi Li , Yunqiu Wang , Qian He , Xinglong Wu
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