RAV4D: A Radar-Audia-Visual Dataset for Indoor Multi - Person Tracking
Author:
Affiliation:
1. School of Advanced Technology Xi'an Jiaotong-Liverpool University,Suzhou,China
2. University of Liverpool,Department of Electrical Engineering and Electronics,Liverpool,UK
3. Institute of Deep Perception Technology JITRI,Wuxi,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10548015/10548012/10549701.pdf?arnumber=10549701
Reference15 articles.
1. Recent advances in em-bedding methods for multi-object tracking: a survey;Wang;arXiv preprint,2022
2. A Survey of Sound Source Localization Methods in Wireless Acoustic Sensor Networks
3. Towards Deep Radar Perception for Autonomous Driving: Datasets, Methods, and Challenges
4. MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking
5. DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motion
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