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We present a novel approach to estimating physical properties of objects from video. Our approach consists of a physics engine and a correction estimator. Starting from the initial observed state, object behavior is simulated forward in…

Computer Vision and Pattern Recognition · Computer Science 2022-06-03 Martin Link , Max Schwarz , Sven Behnke

Current approaches to video analysis of human motion focus on raw pixels or keypoints as the basic units of reasoning. We posit that adding higher-level motion primitives, which can capture natural coarser units of motion such as backswing…

Computer Vision and Pattern Recognition · Computer Science 2021-04-23 Sumith Kulal , Jiayuan Mao , Alex Aiken , Jiajun Wu

While current methods have shown promising progress on estimating 3D human motion from monocular videos, their motion estimates are often physically unrealistic because they mainly consider kinematics. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Yufei Zhang , Jeffrey O. Kephart , Zijun Cui , Qiang Ji

In this paper, we present an end-to-end pipeline for the creation of high-quality animatable volumetric video content of human performances. Going beyond the application of free-viewpoint volumetric video, we allow re-animation and…

Computer Vision and Pattern Recognition · Computer Science 2020-09-03 Anna Hilsmann , Philipp Fechteler , Wieland Morgenstern , Wolfgang Paier , Ingo Feldmann , Oliver Schreer , Peter Eisert

Building a generalizable self-correction system is crucial for robots to recover from failures. Despite advancements in Multimodal Large Language Models (MLLMs) that empower robots with semantic reflection ability for failure, translating…

Robotics · Computer Science 2025-04-22 Wenke Xia , Ruoxuan Feng , Dong Wang , Di Hu

Recovering high-quality 3D human motion in complex scenes from monocular videos is important for many applications, ranging from AR/VR to robotics. However, capturing realistic human-scene interactions, while dealing with occlusions and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-25 Siwei Zhang , Yan Zhang , Federica Bogo , Marc Pollefeys , Siyu Tang

We propose a generative approach to physics-based motion capture. Unlike prior attempts to incorporate physics into tracking that assume the subject and scene geometry are calibrated and known a priori, our approach is automatic and online.…

Computer Vision and Pattern Recognition · Computer Science 2018-12-05 Micha Livne , Leonid Sigal , Marcus A. Brubaker , David J. Fleet

Text-guided human motion generation has drawn significant interest because of its impactful applications spanning animation and robotics. Recently, application of diffusion models for motion generation has enabled improvements in the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-17 Samaneh Azadi , Akbar Shah , Thomas Hayes , Devi Parikh , Sonal Gupta

The production of animation is a resource intensive process in game companies. Therefore, techniques to synthesize animations have been developed. However, these procedural techniques offer limited adaptability by animation artists. In…

Human movement analysis is a key area of research in robotics, biomechanics, and data science. It encompasses tracking, posture estimation, and movement synthesis. While numerous methodologies have evolved over time, a systematic and…

Robotics · Computer Science 2023-05-11 Brenda Elizabeth Olivas-Padilla , Alina Glushkova , Sotiris Manitsaris

This paper presents a novel approach for reconstructing dynamic radiance fields from monocular videos. We integrate kinematics with dynamic radiance fields, bridging the gap between the sparse nature of monocular videos and the real-world…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Woobin Im , Geonho Cha , Sebin Lee , Jumin Lee , Juhyeong Seon , Dongyoon Wee , Sung-Eui Yoon

While computer vision has advanced considerably for general object detection and tracking, the specific problem of fast-moving tiny objects remains underexplored. This paper addresses the significant challenge of detecting and tracking…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Prithvi Raj Singh , Raju Gottumukkala , Anthony S. Maida , Alan B. Barhorst , Vijaya Gopu

Human action recognition is regarded as a key cornerstone in domains such as surveillance or video understanding. Despite recent progress in the development of end-to-end solutions for video-based action recognition, achieving…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Jiawei Chen , Jenson Hsiao , Chiu Man Ho

Recent advances in diffusion models bring new vitality to visual content creation. However, current text-to-video generation models still face significant challenges such as high training costs, substantial data requirements, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Sicong Feng , Jielong Yang , Li Peng

We contribute an analysis of situated visualizations in motion in video games for different types of data, with a focus on quantitative and categorical data representations. Video games convey a lot of data to players, to help them succeed…

Human-Computer Interaction · Computer Science 2024-09-13 Federica Bucchieri , Lijie Yao , Petra Isenberg

Recent works have sought to enhance the controllability and precision of text-driven motion generation. Some approaches leverage large language models (LLMs) to produce more detailed texts, while others incorporate global 3D coordinate…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Keming Shen , Bizhu Wu , Junliang Chen , Xiaoqin Wang , Linlin Shen

Video motion magnification techniques allow us to see small motions previously invisible to the naked eyes, such as those of vibrating airplane wings, or swaying buildings under the influence of the wind. Because the motion is small, the…

Computer Vision and Pattern Recognition · Computer Science 2019-02-18 Tae-Hyun Oh , Ronnachai Jaroensri , Changil Kim , Mohamed Elgharib , Frédo Durand , William T. Freeman , Wojciech Matusik

Current methods for generating human motion videos rely on extracting pose sequences from reference videos, which restricts flexibility and control. Additionally, due to the limitations of pose detection techniques, the extracted pose…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Yuhang Zhang , Yuan Zhou , Zeyu Liu , Yuxuan Cai , Qiuyue Wang , Aidong Men , Huan Yang

Upsampling videos of human activity is an interesting yet challenging task with many potential applications ranging from gaming to entertainment and sports broadcasting. The main difficulty in synthesizing video frames in this setting stems…

Computer Vision and Pattern Recognition · Computer Science 2021-11-02 Hsuan-I Ho , Xu Chen , Jie Song , Otmar Hilliges

Markerless estimation of 3D Kinematics has the great potential to clinically diagnose and monitor movement disorders without referrals to expensive motion capture labs; however, current approaches are limited by performing multiple…

Computer Vision and Pattern Recognition · Computer Science 2023-01-16 Marian Bittner , Wei-Tse Yang , Xucong Zhang , Ajay Seth , Jan van Gemert , Frans C. T. van der Helm
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