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Beyond Labels And Captions: Contextualizing Grounded Semantics For Explainable Visual Interpretation, Sathyanarayanan Narasimhan Aakur

USF Tampa Graduate Theses and Dissertations

One of the long-standing problems in artificial intelligence is the development of intelligent agents with complete visual understanding. Understanding entails recognition of scene attributes such as actors, objects and actions as well as reasoning about the common semantic structure that combines these attributes into a coherent description. While significant milestones have been achieved in the field of computer vision, majority of the work has been concentrated on supervised visual recognition where complex visual representations are learned and a few discrete categories or labels are assigned to these representations. This implies a closed world where the underlying assumption is that all …