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We propose an end-to-end trainable, cross-category method for reconstructing multiple man-made articulated objects from a single RGBD image, focusing on part-level shape reconstruction and pose and kinematics estimation. We depart from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Yuki Kawana , Tatsuya Harada

The dynamics of human skeletons have significant information for the task of action recognition. The similarity between trajectories of corresponding joints is an indicating feature of the same action, while this similarity may subject to…

Computer Vision and Pattern Recognition · Computer Science 2020-04-22 Qi Li , Hanlin Mo , Jinghan Zhao , Hongxiang Hao , Hua Li

With the development of robotics, skeleton-based action recognition has become increasingly important, as human-robot interaction requires understanding the actions of humans and humanoid robots. Due to different sources of human skeletons…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Jidong Kuang , Hongsong Wang , Jie Gui

Estimating the body shape and posture of a dressed human subject in motion represented as a sequence of (possibly incomplete) 3D meshes is important for virtual change rooms and security. To solve this problem, statistical shape spaces…

Computer Vision and Pattern Recognition · Computer Science 2015-03-30 Stefanie Wuhrer , Leonid Pishchulin , Alan Brunton , Chang Shu , Jochen Lang

We introduce a method for manipulating objects in three-dimensional space using controlled fluid streams. To achieve this, we train a neural network controller in a differentiable simulation and evaluate it in a simulated environment…

Robotics · Computer Science 2024-04-30 Karlis Freivalds , Laura Leja , Oskars Teikmanis

Humans possess an exceptional ability to imagine 4D scenes, encompassing both motion and 3D geometry, from a single still image. This ability is rooted in our accumulated observations of similar scenes and an intuitive understanding of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Emily Yue-Ting Jia , Jiageng Mao , Zhiyuan Gao , Yajie Zhao , Yue Wang

We study end-to-end learning strategies for 3D shape inference from images, in particular from a single image. Several approaches in this direction have been investigated that explore different shape representations and suitable learning…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Roman Klokov , Jakob Verbeek , Edmond Boyer

We propose a new family of neural networks to predict the behaviors of physical systems by learning their underpinning constraints. A neural projection operator lies at the heart of our approach, composed of a lightweight network with an…

Neural and Evolutionary Computing · Computer Science 2020-12-15 Shuqi Yang , Xingzhe He , Bo Zhu

Skeleton-based action recognition has made great progress recently, but many problems still remain unsolved. For example, most of the previous methods model the representations of skeleton sequences without abundant spatial structure…

Computer Vision and Pattern Recognition · Computer Science 2018-12-04 Chenyang Si , Ya Jing , Wei Wang , Liang Wang , Tieniu Tan

A topology preserving skeleton is a synthetic representation of an object that retains its topology and many of its significant morphological properties. The process of obtaining the skeleton, referred to as skeletonization or thinning, is…

Computer Vision and Pattern Recognition · Computer Science 2015-06-17 Paweł Dłotko , Ruben Specogna

Shape from texture refers to the extraction of 3D information from 2D images with irregular texture. This paper introduces a statistical framework to learn shape from texture where convex texture elements in a 2D image are represented…

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

We propose a scalable neural network framework to reconstruct the 3D mesh of a human body from multi-view images, in the subspace of the SMPL model. Use of multi-view images can significantly reduce the projection ambiguity of the problem,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-27 Junbang Liang , Ming C. Lin

We present a new method for the analysis of images, a fundamental task in observational astronomy. It is based on the linear decomposition of each object in the image into a series of localised basis functions of different shapes, which we…

Astrophysics · Physics 2008-11-26 Alexandre Refregier

Modeling fluid turbulence using a 'skeleton' of coherent structures has traditionally progressed by focusing on a few canonical experiments, such as pipe flow and Taylor-Couette flow. We here consider an alternative canonical experiment,…

Fluid Dynamics · Physics 2023-05-09 Adrien Lefauve , Miles M. P. Couchman

This paper introduces a framework based on linear splines for 2-dimensional extended object tracking and classification. Unlike state of the art models, linear splines allow to represent extended objects whose contour is an arbitrarily…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Matteo Tesori , Giorgio Battistelli , Luigi Chisci

In various applications, such as virtual reality and gaming, simulating the deformation of soft tissues in the human body during interactions with external objects is essential. Traditionally, Finite Element Methods (FEM) have been employed…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Anton Agafonov , Lihi Zelnik-Manor

In this work, we consider two kinds of model reduction techniques to simulate blood flow through the largest systemic arteries, where a stenosis is located in a peripheral artery i.e. in an artery that is located far away from the heart.…

Numerical Analysis · Mathematics 2018-10-09 Tobias Köppl , Gabriele Santin , Bernard Haasdonk , Rainer Helmig

In many real-world settings, image observations of freely rotating 3D rigid bodies may be available when low-dimensional measurements are not. However, the high-dimensionality of image data precludes the use of classical estimation…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Justice Mason , Christine Allen-Blanchette , Nicholas Zolman , Elizabeth Davison , Naomi Ehrich Leonard

Manipulating deformable objects remains a challenge within robotics due to the difficulties of state estimation, long-horizon planning, and predicting how the object will deform given an interaction. These challenges are the most pronounced…

Robotics · Computer Science 2024-03-18 Alison Bartsch , Arvind Car , Charlotte Avra , Amir Barati Farimani