Video Person Re-ID: Fantastic Techniques and Where to Find Them
November 21, 2019 Β· Declared Dead Β· π AAAI Conference on Artificial Intelligence
"No code URL or promise found in abstract"
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Authors
Priyank Pathak, Amir Erfan Eshratifar, Michael Gormish
arXiv ID
1912.05295
Category
cs.CV: Computer Vision
Citations
28
Venue
AAAI Conference on Artificial Intelligence
Last Checked
5 months ago
Abstract
The ability to identify the same person from multiple camera views without the explicit use of facial recognition is receiving commercial and academic interest. The current status-quo solutions are based on attention neural models. In this paper, we propose Attention and CL loss, which is a hybrid of center and Online Soft Mining (OSM) loss added to the attention loss on top of a temporal attention-based neural network. The proposed loss function applied with bag-of-tricks for training surpasses the state of the art on the common person Re-ID datasets, MARS and PRID 2011. Our source code is publicly available on github.
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