Work

Multi-Person Human-Centric Motion Understanding for Complex Coordinated Activities

Year: 2026

Type: preprint

Abstract: Understanding coordinated human activities involving multiple interacting people — such as team sports, group dance, or collaborative physical tasks — requires reasoning not just about individual pose and motion but about the relational and temporal coordination between multiple people simultaneously. This project proposes a multi-person, human-centric motion understanding framework that jointly models individual pose dynamics and inter-person coordination patterns to recognize and analyze complex coordinated activities from video.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22021948

Author: GUPTA, ADISHREE

Language: English

Topic: Human Pose and Action Recognition

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7203917424

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