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Related papers: Recovering Articulated Object Models from 3D Range…

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Articulated objects are ubiquitous in daily life. Our goal is to achieve a high-quality reconstruction, segmentation of independent moving parts, and analysis of articulation. Recent methods analyse two different articulation states and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Hao Ai , Wenjie Chang , Jianbo Jiao , Ales Leonardis , Ofek Eyal

Creating high-quality articulated 3D models of animals is challenging either via manual creation or using 3D scanning tools. Therefore, techniques to reconstruct articulated 3D objects from 2D images are crucial and highly useful. In this…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Chun-Han Yao , Wei-Chih Hung , Yuanzhen Li , Michael Rubinstein , Ming-Hsuan Yang , Varun Jampani

This paper presents a fully automatic framework for extracting editable 3D objects directly from a single photograph. Unlike previous methods which recover either depth maps, point clouds, or mesh surfaces, we aim to recover 3D objects with…

Computer Vision and Pattern Recognition · Computer Science 2020-05-29 Xin Chen , Yuwei Li , Xi Luo , Tianjia Shao , Jingyi Yu , Kun Zhou , Youyi Zheng

Articulation perception aims to recover the motion and structure of articulated objects (e.g., drawers and cupboards), and is fundamental to 3D scene understanding in robotics, simulation, and animation. Existing learning-based methods rely…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Yihao Wang , Yang Miao , Wenshuai Zhao , Wenyan Yang , Zihan Wang , Joni Pajarinen , Luc Van Gool , Danda Pani Paudel , Juho Kannala , Xi Wang , Arno Solin

We propose a novel approach for unsupervised 3D animation of non-rigid deformable objects. Our method learns the 3D structure and dynamics of objects solely from single-view RGB videos, and can decompose them into semantically meaningful…

Computer Vision and Pattern Recognition · Computer Science 2023-01-27 Aliaksandr Siarohin , Willi Menapace , Ivan Skorokhodov , Kyle Olszewski , Jian Ren , Hsin-Ying Lee , Menglei Chai , Sergey Tulyakov

Object reconstruction is an important task in many fields of application as it allows to generate digital representations of our physical world used as base for analysis, planning, construction, visualization or other aims. A reconstruction…

We address the novel task of jointly reconstructing the 3D shape, texture, and motion of an object from a single motion-blurred image. While previous approaches address the deblurring problem only in the 2D image domain, our proposed…

Computer Vision and Pattern Recognition · Computer Science 2021-10-27 Denys Rozumnyi , Martin R. Oswald , Vittorio Ferrari , Marc Pollefeys

Mesh models are a promising approach for encoding the structure of 3D objects. Current mesh reconstruction systems predict uniformly distributed vertex locations of a predetermined graph through a series of graph convolutions, leading to…

Computer Vision and Pattern Recognition · Computer Science 2019-02-01 Edward J. Smith , Scott Fujimoto , Adriana Romero , David Meger

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

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

This paper presents a novel framework to recover \emph{detailed} avatar from a single image. It is a challenging task due to factors such as variations in human shapes, body poses, texture, and viewpoints. Prior methods typically attempt to…

Computer Vision and Pattern Recognition · Computer Science 2021-08-21 Hao Zhu , Xinxin Zuo , Haotian Yang , Sen Wang , Xun Cao , Ruigang Yang

This research proposes a novel adjustable algorithm for reconstructing 3D body shapes from front and side silhouettes. Most recent silhouette-based approaches use a deep neural network trained by silhouettes and key points to estimate the…

Computer Vision and Pattern Recognition · Computer Science 2023-01-03 Aref Hemati , Azam Bastanfard

Understanding how an animal can deform and articulate is essential for a realistic modification of its 3D model. In this paper, we show that such information can be learned from user-clicked 2D images and a template 3D model of the target…

Computer Vision and Pattern Recognition · Computer Science 2016-05-25 Angjoo Kanazawa , Shahar Kovalsky , Ronen Basri , David W. Jacobs

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

Advancing robotic manipulation of deformable objects can enable automation of repetitive tasks across multiple industries, from food processing to textiles and healthcare. Yet robots struggle with the high dimensionality of deformable…

Robotics · Computer Science 2024-09-26 Jan Obrist , Miguel Zamora , Hehui Zheng , Juan Zarate , Robert K. Katzschmann , Stelian Coros

In this work, we focus on the task of learning and representing dense correspondences in deformable object categories. While this problem has been considered before, solutions so far have been rather ad-hoc for specific object types (i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2020-11-26 Natalia Neverova , David Novotny , Vasil Khalidov , Marc Szafraniec , Patrick Labatut , Andrea Vedaldi

Non-parametric mesh reconstruction has recently shown significant progress in 3D hand and body applications. In these methods, mesh vertices and edges are visible to neural networks, enabling the possibility to establish a direct mapping…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Shijian Jiang , Guwen Han , Danhang Tang , Yang Zhou , Xiang Li , Jiming Chen , Qi Ye

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

Estimating the pose and shape of hands and objects under interaction finds numerous applications including augmented and virtual reality. Existing approaches for hand and object reconstruction require explicitly defined physical constraints…

Computer Vision and Pattern Recognition · Computer Science 2022-04-28 Tze Ho Elden Tse , Kwang In Kim , Ales Leonardis , Hyung Jin Chang

We reconstruct 3D deformable object through time, in the context of a live pottery making process where the crafter molds the object. Because the object suffers from heavy hand interaction, and is being deformed, classical techniques cannot…

Computer Vision and Pattern Recognition · Computer Science 2019-08-06 Raoul de Charette , Sotiris Manitsaris
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