You're currently viewing an old version of this dataset. To see the current version, click here.

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.

Data and Resources

This dataset has no data

Cite this as

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

Private DOI This DOI is not yet resolvable.
It is available for use in manuscripts, and will be published when the Dataset is made public.

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