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Weakly-Supervised Object Localization

Weakly supervised object localization (WSOL) learns to localize objects with only image-level labels, no object level labels (bonding boxes, etc.,) is needed. It is more attractive since image-level labels are much easier and cheaper to obtain.

Papers

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Showing 61–70 of 140 papers

TitleStatusHype
Erasing Integrated Learning: A Simple Yet Effective Approach for Weakly Supervised Object Localization—0
Weakly-supervised Object Localization for Few-shot Learning and Fine-grained Few-shot Learning—0
Fine-Grained Attention for Weakly Supervised Object Localization—0
Foreground Activation Maps for Weakly Supervised Object Localization—0
Hierarchical Complementary Learning for Weakly Supervised Object Localization—0
How hard can it be? Estimating the difficulty of visual search in an image—0
Improved Techniques For Weakly-Supervised Object Localization—0
Improving Few-shot Learning with Weakly-supervised Object Localization—0
Improving Weakly-Supervised Object Localization By Micro-Annotation—0
Improving Weakly-Supervised Object Localization Using Adversarial Erasing and Pseudo Label—0
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