April 8, 2024, 4:44 a.m. | Rui Wang, Chuanfu Shen, Manuel J. Marin-Jimenez, George Q. Huang, Shiqi Yu

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.04120v1 Announce Type: new
Abstract: Current gait recognition research mainly focuses on identifying pedestrians captured by the same type of sensor, neglecting the fact that individuals may be captured by different sensors in order to adapt to various environments. A more practical approach should involve cross-modality matching across different sensors. Hence, this paper focuses on investigating the problem of cross-modality gait recognition, with the objective of accurately identifying pedestrians across diverse vision sensors. We present CrossGait inspired by the feature …

abstract adapt arxiv cs.cv current environments human identification lidar pedestrians practical recognition research sensor sensors 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

#13721 - Data Engineer - AI Model Testing

@ Qualitest | Miami, Florida, United States

Elasticsearch Administrator

@ ManTech | 201BF - Customer Site, Chantilly, VA