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In this technical report, we investigate efficient representations of articulated objects (e.g. human bodies), which is an important problem in computer vision and graphics. To deform articulated geometry, existing approaches represent…

Realtime shape estimation of continuum objects and manipulators is essential for developing accurate planning and control paradigms. The existing methods that create dense point clouds from camera images, and/or use distinguishable markers…

Robotics · Computer Science 2024-10-23 Jiaming Zhang , Zhaomeng Zhang , Yihao Liu , Yaqian Chen , Amir Kheradmand , Mehran Armand

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

This paper propose a interactive 3D modeling method and corresponding system based on single or multiple uncalibrated images. The main feature of this method is that, according to the modeling habits of ordinary people, the 3D model of the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zhi He , Rui Wang , Wei Hua , Yuchi Huo

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

We present Deep Shape-from-Template (DeepSfT), a novel Deep Neural Network (DNN) method for solving real-time automatic registration and 3D reconstruction of a deformable object viewed in a single monocular image.DeepSfT advances the…

Computer Vision and Pattern Recognition · Computer Science 2021-03-02 David Fuentes-Jimenez , David Casillas-Perez , Daniel Pizarro , Toby Collins , Adrien Bartoli

This paper shows that it is possible to learn models for monocular 3D reconstruction of articulated objects (e.g., horses, cows, sheep), using as few as 50-150 images labeled with 2D keypoints. Our proposed approach involves training…

Computer Vision and Pattern Recognition · Computer Science 2023-04-28 Anastasis Stathopoulos , Georgios Pavlakos , Ligong Han , Dimitris Metaxas

High-quality 4D reconstruction of human performance with complex interactions to various objects is essential in real-world scenarios, which enables numerous immersive VR/AR applications. However, recent advances still fail to provide…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Zhuo Su , Lan Xu , Dawei Zhong , Zhong Li , Fan Deng , Shuxue Quan , Lu Fang

We propose a method for constructing generative models of 3D objects from a single 3D mesh. Our method produces a 3D morphable model that represents shape and albedo in terms of Gaussian processes. We define the shape deformations in…

Computer Vision and Pattern Recognition · Computer Science 2021-10-04 Skylar Sutherland , Bernhard Egger , Joshua Tenenbaum

Skeleton generation is essential for animating 3D assets, but current deep learning methods remain limited: they cannot handle the growing structural complexity of modern models and offer minimal controllability, creating a major bottleneck…

In this paper, we propose ARCH (Animatable Reconstruction of Clothed Humans), a novel end-to-end framework for accurate reconstruction of animation-ready 3D clothed humans from a monocular image. Existing approaches to digitize 3D humans…

Graphics · Computer Science 2020-04-14 Zeng Huang , Yuanlu Xu , Christoph Lassner , Hao Li , Tony Tung

Tracking and reconstructing 3D objects from cluttered scenes are the key components for computer vision, robotics and autonomous driving systems. While recent progress in implicit function has shown encouraging results on high-quality 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Jianglong Ye , Yuntao Chen , Naiyan Wang , Xiaolong Wang

Skeletonization is a popular shape analysis technique that models an object's interior as opposed to just its boundary. Fitting template-based skeletal models is a time-consuming process requiring much manual parameter tuning. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Nicolás Gaggion , Enzo Ferrante , Beatriz Paniagua , Jared Vicory

Object-centric reconstruction seeks to recover the 3D structure of a scene through composition of independent objects. While this independence can simplify modeling, it discards strong signals that could improve reconstruction, notably…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Qirui Wu , Yawar Siddiqui , Duncan Frost , Samir Aroudj , Armen Avetisyan , Richard Newcombe , Angel X. Chang , Jakob Engel , Henry Howard-Jenkins

Many compelling video post-processing effects, in particular aesthetic focus editing and refocusing effects, are feasible if per-frame depth information is available. Existing computational methods to capture RGB and depth either…

Computer Vision and Pattern Recognition · Computer Science 2016-10-13 Hyeongwoo Kim , Christian Richardt , Christian Theobalt

Standard RGB-D trackers treat the target as an inherently 2D structure, which makes modelling appearance changes related even to simple out-of-plane rotation highly challenging. We address this limitation by proposing a novel long-term…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 Ugur Kart , Alan Lukezic , Matej Kristan , Joni-Kristian Kamarainen , Jiri Matas

Tracking mouse body parts in video is often incomplete due to occlusions such that - e.g. - subsequent action and behavior analysis is impeded. In this conceptual work, videos from several perspectives are integrated via global exterior…

Existing methods for 3D tracking from monocular RGB videos predominantly consider articulated and rigid objects. Modelling dense non-rigid object deformations in this setting remained largely unaddressed so far, although such effects can…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 Soshi Shimada , Vladislav Golyanik , Patrick Pérez , Christian Theobalt

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

Tracking and reconstructing the 3D pose and geometry of two hands in interaction is a challenging problem that has a high relevance for several human-computer interaction applications, including AR/VR, robotics, or sign language…

Computer Vision and Pattern Recognition · Computer Science 2021-06-23 Jiayi Wang , Franziska Mueller , Florian Bernard , Suzanne Sorli , Oleksandr Sotnychenko , Neng Qian , Miguel A. Otaduy , Dan Casas , Christian Theobalt
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