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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 1–10 of 142 papers

TitleStatusHype
Self-Supervised Transformers for Unsupervised Object Discovery using Normalized CutCode2
WeakSAM: Segment Anything Meets Weakly-supervised Instance-level RecognitionCode2
Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in DrawingsCode1
Cyclic-Bootstrap Labeling for Weakly Supervised Object DetectionCode1
Comprehensive Attention Self-Distillation for Weakly-Supervised Object DetectionCode1
Domain-Adaptive Object Detection via Uncertainty-Aware Distribution AlignmentCode1
Boosting Weakly Supervised Object Detection with Progressive Knowledge TransferCode1
Active Learning Strategies for Weakly-supervised Object DetectionCode1
Boosting Weakly Supervised Object Detection via Learning Bounding Box AdjustersCode1
Cross-Domain Weakly-Supervised Object Detection through Progressive Domain AdaptationCode1
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