ABD-Net: Attentive but Diverse Person Re-Identification

Attention mechanisms have been found effective for person re-identification (Re-ID). However, the learned "attentive'' features are often not naturally uncorrelated or "diverse'', which compromises the retrieval performance based on the Euclidean distance. We advocate the complementary powers of attention and diversity for Re-ID, by proposing an Attentive but Diverse Network (ABD-Net). ABD-Net seamlessly integrates attention modules and diversity regularizations throughout the entire network to learn features that are representative, robust, and more discriminative. Specifically, we introduce a pair of complementary attention modules, focusing on channel aggregation and position awareness, respectively. Then,…