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Learning Discriminative And Efficient Attention For Person Re-Identification Using Agglomerative Clustering Frameworks, Kshitij Nikhal

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Recent advancements like multiple contextual analysis, attention mechanisms, distance-aware optimization, and multi-task guidance have been widely used for supervised person re-identification (ReID), but the implementation and effects of such methods in unsupervised person ReID frameworks are non-trivial and unclear, respectively. Moreover, with increasing size and complexity of image- and video-based ReID datasets, manual or semi-automated annotation procedures for supervised ReID are becoming labor intensive and cost prohibitive, which is undesirable especially considering the likelihood of annotation errors increase with scale/complexity of data collections. Therefore, this thesis proposes a new iterative clustering framework that incorporates (a) two attention architectures that learn …