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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

Generating 3D shapes at part level is pivotal for downstream applications such as mesh retopology, UV mapping, and 3D printing. However, existing part-based generation methods often lack sufficient controllability and suffer from poor…

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

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

Part-level 3D generation is essential for applications requiring decomposable and structured 3D synthesis. However, existing methods either rely on implicit part segmentation with limited granularity control or depend on strong external…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Xufan He , Yushuang Wu , Xiaoyang Guo , Chongjie Ye , Jiaqing Zhou , Tianlei Hu , Xiaoguang Han , Dong Du

Generating stylized 3D human motion from speech signals presents substantial challenges, primarily due to the intricate and fine-grained relationships among speech signals, individual styles, and the corresponding body movements. Current…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Lianlian Liu , YongKang He , Zhaojie Chu , Xiaofen Xing , Xiangmin Xu

Text- or image-to-3D generators and 3D scanners can now produce 3D assets with high-quality shapes and textures. These assets typically consist of a single, fused representation, like an implicit neural field, a Gaussian mixture, or a mesh,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Minghao Chen , Roman Shapovalov , Iro Laina , Tom Monnier , Jianyuan Wang , David Novotny , Andrea Vedaldi

We introduce AutoPartGen, a model that generates objects composed of 3D parts in an autoregressive manner. This model can take as input an image of an object, 2D masks of the object's parts, or an existing 3D object, and generate a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Minghao Chen , Jianyuan Wang , Roman Shapovalov , Tom Monnier , Hyunyoung Jung , Dilin Wang , Rakesh Ranjan , Iro Laina , Andrea Vedaldi

We present the Shape Part Slot Machine, a new method for assembling novel 3D shapes from existing parts by performing contact-based reasoning. Our method represents each shape as a graph of ``slots,'' where each slot is a region of contact…

Graphics · Computer Science 2022-07-25 Kai Wang , Paul Guerrero , Vladimir Kim , Siddhartha Chaudhuri , Minhyuk Sung , Daniel Ritchie

Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares. However, due to its irregular structure, mesh creation and manipulation is often time-consuming and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhaoyang Lyu , Ben Fei , Jinyi Wang , Xudong Xu , Ya Zhang , Weidong Yang , Bo Dai

Interactable objects are ubiquitous in our daily lives. Recent advances in 3D generative models make it possible to automate the modeling of these objects, benefiting a range of applications from 3D printing to the creation of robot…

Computer Vision and Pattern Recognition · Computer Science 2025-02-05 Rundong Luo , Haoran Geng , Congyue Deng , Puhao Li , Zan Wang , Baoxiong Jia , Leonidas Guibas , Siyuan Huang

Recent advances in 3D generation have transitioned from multi-view 2D rendering approaches to 3D-native latent diffusion frameworks that exploit geometric priors in ground truth data. Despite progress, three key limitations persist: (1)…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Shaocong Dong , Lihe Ding , Xiao Chen , Yaokun Li , Yuxin Wang , Yucheng Wang , Qi Wang , Jaehyeok Kim , Chenjian Gao , Zhanpeng Huang , Zibin Wang , Tianfan Xue , Dan Xu

Part-based 3D generation holds great potential for various applications. Previous part generators that represent parts using implicit vector-set tokens often suffer from insufficient geometric details. Another line of work adopts an…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Lihe Ding , Shaocong Dong , Yaokun Li , Chenjian Gao , Xiao Chen , Rui Han , Yihao Kuang , Hong Zhang , Bo Huang , Zhanpeng Huang , Zibin Wang , Dan Xu , Tianfan Xue

We introduce PartCrafter, the first structured 3D generative model that jointly synthesizes multiple semantically meaningful and geometrically distinct 3D meshes from a single RGB image. Unlike existing methods that either produce…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Yuchen Lin , Chenguo Lin , Panwang Pan , Honglei Yan , Yiqiang Feng , Yadong Mu , Katerina Fragkiadaki

Part-level 3D generation is crucial for various downstream applications, including gaming, film production, and industrial design. However, decomposing a 3D shape into geometrically plausible and meaningful components remains a significant…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Wanhu Sun , Zhongjin Luo , Heliang Zheng , Jiahao Chang , Chongjie Ye , Huiang He , Shengchu Zhao , Rongfei Jia , Xiaoguang Han

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

Manually authoring 3D shapes is difficult and time consuming; generative models of 3D shapes offer compelling alternatives. Procedural representations are one such possibility: they offer high-quality and editable results but are difficult…

We address the challenge of generating 3D articulated objects in a controllable fashion. Currently, modeling articulated 3D objects is either achieved through laborious manual authoring, or using methods from prior work that are hard to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Jiayi Liu , Hou In Ivan Tam , Ali Mahdavi-Amiri , Manolis Savva

Manually creating 3D environments for AR/VR applications is a complex process requiring expert knowledge in 3D modeling software. Pioneering works facilitate this process by generating room meshes conditioned on textual style descriptions.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Jonas Schult , Sam Tsai , Lukas Höllein , Bichen Wu , Jialiang Wang , Chih-Yao Ma , Kunpeng Li , Xiaofang Wang , Felix Wimbauer , Zijian He , Peizhao Zhang , Bastian Leibe , Peter Vajda , Ji Hou

The advent of large language models, enabling flexibility through instruction-driven approaches, has revolutionized many traditional generative tasks, but large models for 3D data, particularly in comprehensively handling 3D shapes with…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Fukun Yin , Xin Chen , Chi Zhang , Biao Jiang , Zibo Zhao , Jiayuan Fan , Gang Yu , Taihao Li , Tao Chen
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