The Devil is in the Details: Self-Supervised Attention for Vehicle Re-Identification

14 Apr 2020Pirazh KhorramshahiNeehar PeriJun-cheng ChenRama Chellappa

In recent years, the research community has approached the problem of vehicle re-identification (re-id) with attention-based models, specifically focusing on regions of a vehicle containing discriminative information. These re-id methods rely on expensive key-point labels, part annotations, and additional attributes including vehicle make, model, and color... (read more)

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