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Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification
[article]
2018
arXiv
pre-print
Video-based person re-identification (re-id) is a central application in surveillance systems with significant concern in security. Matching persons across disjoint camera views in their video fragments is inherently challenging due to the large visual variations and uncontrolled frame rates. There are two steps crucial to person re-id, namely discriminative feature learning and metric learning. However, existing approaches consider the two steps independently, and they do not make full use of
arXiv:1808.01911v2
fatcat:hl64uomz4vfwpihbmelosrtkdi