Visual Concept Recognition and Localization via Iterative Introspection

doi:doi:10.57702/qof0zedi

Visual Concept Recognition and Localization via Iterative Introspection

The proposed method alternates classiﬁcation and introspection. The introspection phase employs a strategy to select a sub-window for the next step by applying a beam-search to a set of putative sub-windows.

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Amir Rosenfeld, Shimon Ullman (2024). Dataset: Visual Concept Recognition and Localization via Iterative Introspection. https://doi.org/10.57702/qof0zedi

DOI retrieved: December 17, 2024

Additional Info

Field	Value
Created	December 17, 2024
Last update	December 17, 2024
Defined In	https://doi.org/10.48550/arXiv.1603.04186
Author	Amir Rosenfeld
More Authors	Shimon Ullman
Homepage	https://arxiv.org/abs/1512.04150