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Multiple Expert Brainstorming for Domain Adaptive Person Re-identification
[article]
2020
arXiv
pre-print
Often the best performing deep neural models are ensembles of multiple base-level networks, nevertheless, ensemble learning with respect to domain adaptive person re-ID remains unexplored. In this paper, we propose a multiple expert brainstorming network (MEB-Net) for domain adaptive person re-ID, opening up a promising direction about model ensemble problem under unsupervised conditions. MEB-Net adopts a mutual learning strategy, where multiple networks with different architectures are
arXiv:2007.01546v3
fatcat:m66wzjbigjbxtohccg4psa4oue