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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 11–20 of 142 papers

TitleStatusHype
LEOD: Label-Efficient Object Detection for Event CamerasCode1
Max Pooling with Vision Transformers reconciles class and shape in weakly supervised semantic segmentationCode1
Cyclic-Bootstrap Labeling for Weakly Supervised Object DetectionCode1
Multiple instance learning on deep features for weakly supervised object detection with extreme domain shiftsCode1
Active Learning Strategies for Weakly-supervised Object DetectionCode1
Distilling Knowledge from Refinement in Multiple Instance Detection NetworksCode1
Boosting Weakly Supervised Object Detection with Progressive Knowledge TransferCode1
Domain-Adaptive Object Detection via Uncertainty-Aware Distribution AlignmentCode1
Comprehensive Attention Self-Distillation for Weakly-Supervised Object DetectionCode1
H2FA R-CNN: Holistic and Hierarchical Feature Alignment for Cross-Domain Weakly Supervised Object DetectionCode1
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