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Weakly Supervised Object Detection

Weakly Supervised Object Detection (WSOD) is the task of training object detectors with only image tag supervisions.

( Image credit: Soft Proposal Networks for Weakly Supervised Object Localization )

Papers

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Showing 111–120 of 142 papers

TitleStatusHype
Weakly Supervised Region Proposal Network and Object Detection—0
TS2C: Tight Box Mining with Surrounding Segmentation Context for Weakly Supervised Object Detection—0
W2F: A Weakly-Supervised to Fully-Supervised Framework for Object Detection—0
Generative Adversarial Learning Towards Fast Weakly Supervised Detection—0
Zigzag Learning for Weakly Supervised Object Detection—0
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning—0
Collaborative Learning for Weakly Supervised Object Detection—0
Weakly Supervised Object Detection with Pointwise Mutual Information—0
Multiple Instance Curriculum Learning for Weakly Supervised Object Detection—0
Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks—0
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