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.
@article{arxiv.1912.05295,
title = {Video Person Re-ID: Fantastic Techniques and Where to Find Them},
author = {Priyank Pathak and Amir Erfan Eshratifar and Michael Gormish},
journal= {arXiv preprint arXiv:1912.05295},
year = {2019}
}