Event-Guided Person Re-Identification via Sparse-Dense Complementary Learning
Author:
Affiliation:
1. University of Science and Technology of China,China
2. University of Rochester,USA
Funder
National Key R&D Program of China
National Natural Science Foundation of China (NSFC)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203615.pdf?arnumber=10203615
Reference61 articles.
1. Mathias Gehrig, Mario Millhäusler, Daniel Gehrig, and Davide Scaramuzza;E-RAFT Dense Optical Flow from Event Cameras,2021
2. MARS: A Video Benchmark for Large-Scale Person Re-Identification;zheng;ECCV,2016
3. Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-Based Person Re-Identification
4. Temporal Knowledge Propagation for Image-to-Video Person Re-Identification
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