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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 21–30 of 142 papers

TitleStatusHype
Domain-Adaptive Object Detection via Uncertainty-Aware Distribution AlignmentCode1
Comprehensive Attention Self-Distillation for Weakly-Supervised Object DetectionCode1
Multiple instance learning on deep features for weakly supervised object detection with extreme domain shiftsCode1
Boosting Weakly Supervised Object Detection with Progressive Knowledge TransferCode1
Distilling Knowledge from Refinement in Multiple Instance Detection NetworksCode1
Instance-aware, Context-focused, and Memory-efficient Weakly Supervised Object DetectionCode1
Harmonizing Transferability and Discriminability for Adapting Object DetectorsCode1
Object Instance Mining for Weakly Supervised Object DetectionCode1
Towards Precise End-to-end Weakly Supervised Object Detection NetworkCode1
Weakly Supervised Object Detection in ArtworksCode1
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