March 26, 2024, 4:46 a.m. | Sihan Ma, Qiong Cao, Jing Zhang, Dacheng Tao

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.15709v1 Announce Type: new
Abstract: This paper addresses the problem of generating 3D interactive human motion from text. Given a textual description depicting the actions of different body parts in contact with objects, we synthesize sequences of 3D body poses that are visually natural and physically plausible. Yet, this task poses a significant challenge due to the inadequate consideration of interactions by physical contacts in both motion and textual descriptions, leading to unnatural and implausible sequences. To tackle this challenge, …

abstract arxiv cs.ai cs.cv human interactive natural objects paper text textual type

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Senior ML Engineer

@ Carousell Group | Ho Chi Minh City, Vietnam

Data and Insight Analyst

@ Cotiviti | Remote, United States