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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 31–40 of 142 papers

TitleStatusHype
Active Learning Strategies for Weakly-supervised Object DetectionCode1
Distilling Knowledge from Refinement in Multiple Instance Detection NetworksCode1
Domain-Adaptive Object Detection via Uncertainty-Aware Distribution AlignmentCode1
Class Agnostic Instance-level Descriptor for Visual Instance Search—0
Discovery-and-Selection: Towards Optimal Multiple Instance Learning for Weakly Supervised Object Detection—0
DETR with Additional Global Aggregation for Cross-domain Weakly Supervised Object Detection—0
Deep Self-Taught Learning for Weakly Supervised Object Localization—0
Absolute Wrong Makes Better: Boosting Weakly Supervised Object Detection via Negative Deterministic Information—0
Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection—0
Deep Learning for Weakly-Supervised Object Detection and Object Localization: A Survey—0
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