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Panoptic tracking enables pixel-level scene interpretation of videos by integrating instance tracking in panoptic segmentation. This provides robots with a spatio-temporal understanding of the environment, an essential attribute for their…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Juana Valeria Hurtado , Sajad Marvi , Rohit Mohan , Abhinav Valada

Impossible objects, geometric constructions that humans can perceive but that cannot exist in real life, have been a topic of intrigue in visual arts, perception, and graphics, yet no satisfying computer representation of such objects…

Random fields are mathematical structures used to model the spatial interaction of random variables along time, with applications ranging from statistical physics and thermodynamics to system's biology and the simulation of complex systems.…

Information Theory · Computer Science 2021-11-09 Alexandre L. M. Levada

The length of the geodesic between two data points along a Riemannian manifold, induced by a deep generative model, yields a principled measure of similarity. Current approaches are limited to low-dimensional latent spaces, due to the…

Real-time in-between motion generation is universally required in games and highly desirable in existing animation pipelines. Its core challenge lies in the need to satisfy three critical conditions simultaneously: quality, controllability…

Graphics · Computer Science 2022-05-06 Xiangjun Tang , He Wang , Bo Hu , Xu Gong , Ruifan Yi , Qilong Kou , Xiaogang Jin

This paper proposes a novel application system for the generation of three-dimensional (3D) character animation driven by markerless human body motion capturing. The entire pipeline of the system consists of five stages: 1) the capturing of…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Jinbao Wang , Ke Lu , Jian Xue

A large number of powerful, high-quality, and open-source simulation packages exist to efficiently perform molecular dynamics simulations, and their prevalence has greatly accelerated discoveries across a wide range of scientific domains.…

Soft Condensed Matter · Physics 2024-05-01 Toler H. Webb , Daniel M. Sussman

Recent work in unsupervised multi-object segmentation shows impressive results by predicting motion from a single image despite the inherent ambiguity in predicting motion without the next image. On the other hand, the set of possible…

Computer Vision and Pattern Recognition · Computer Science 2023-07-18 Sadra Safadoust , Fatma Güney

In high-end visual effects pipelines, a customized (and expensive) light stage system is (typically) used to scan an actor in order to acquire both geometry and texture for various expressions. Aiming towards democratization, we propose a…

Graphics · Computer Science 2024-01-31 Yilin Zhu , Dalton Omens , Haodi He , Ron Fedkiw

Matching deformable objects using their shapes is an important problem in computer vision since shape is perhaps the most distinguishable characteristic of an object. The problem is difficult due to many factors such as intra-class…

Computer Vision and Pattern Recognition · Computer Science 2015-04-28 Smit Marvaniya , Raj Gupta , Anurag Mittal

We analyze a variational time discretization of geodesic calculus on finite- and certain classes of infinite-dimensional Riemannian manifolds. We investigate the fundamental properties of discrete geodesics, the associated discrete…

Numerical Analysis · Mathematics 2013-03-25 Martin Rumpf , Benedikt Wirth

This paper addresses the morphing of manifold-valued images based on the time discrete geodesic paths model of Berkels, Effland and Rumpf 2015. Although for our manifold-valued setting such an interpretation of the energy functional is not…

Numerical Analysis · Mathematics 2018-05-09 Sebastian Neumayer , Johannes Persch , Gabriele Steidl

Deriving sophisticated 3D motions from sparse keyframes is a particularly challenging problem, due to continuity and exceptionally skeletal precision. The action features are often derivable accurately from the full series of keyframes, and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Clinton Ansun Mo , Kun Hu , Chengjiang Long , Zhiyong Wang

We develop a new method for visualizing and refining the invariances of learned representations. Specifically, we test for a general form of invariance, linearization, in which the action of a transformation is confined to a low-dimensional…

Computer Vision and Pattern Recognition · Computer Science 2020-07-28 Olivier J. Hénaff , Eero P. Simoncelli

In this paper, we present a solution for arbitrary 3D character deformation by investigating rotation angle of decomposition and preserving the mesh topology structure. In computer graphics, skeleton extraction and skeleton-driven animation…

Computer Vision and Pattern Recognition · Computer Science 2016-08-18 Hugo Martin , Raphael Fernandez , Yong Khoo

Robotic manipulation of unfamiliar objects in new environments is challenging and requires extensive training or laborious pre-programming. We propose a new skill transfer framework, which enables a robot to transfer complex object…

Deep generative models learn a mapping from a low dimensional latent space to a high-dimensional data space. Under certain regularity conditions, these models parameterize nonlinear manifolds in the data space. In this paper, we investigate…

Machine Learning · Computer Science 2017-11-23 Hang Shao , Abhishek Kumar , P. Thomas Fletcher

This paper studies a specific metric on plane curves that has the property of being isometric to classical manifold (sphere, complex projective, Stiefel, Grassmann) modulo change of parametrization, each of these classical manifolds being…

Differential Geometry · Mathematics 2008-05-05 Peter W. Michor , David Mumford , Jayant Shah , Laurent Younes

Stylized motion breathes life into characters. However, the fixed skeleton structure and style representation hinder existing data-driven motion synthesis methods from generating stylized motion for various characters. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Jiaxu Zhang , Xin Chen , Gang Yu , Zhigang Tu

We present Neural Generalized Implicit Functions(Neural-GIF), to animate people in clothing as a function of the body pose. Given a sequence of scans of a subject in various poses, we learn to animate the character for new poses. Existing…

Computer Vision and Pattern Recognition · Computer Science 2021-08-23 Garvita Tiwari , Nikolaos Sarafianos , Tony Tung , Gerard Pons-Moll