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Weakly Supervised Object Detection On 2

Metrics

MAP

Results

Performance results of various models on this benchmark

		Paper Title	Repository
H2FA R-CNN (clipart_all)	69.8	H2FA R-CNN: Holistic and Hierarchical Feature Alignment for Cross-Domain Weakly Supervised Object Detection	-
DASS-Detector (YOLOX Tiny)	64.25	Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings
H2FA R-CNN (clipart_test)	55.3	H2FA R-CNN: Holistic and Hierarchical Feature Alignment for Cross-Domain Weakly Supervised Object Detection	-
ICCM	46.7	Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection	-
DT+PL	46.0	Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation
MEAA	41.1	Domain-Adaptive Object Detection via Uncertainty-Aware Distribution Alignment	-
MI-max	38.4	Multiple instance learning on deep features for weakly supervised object detection with extreme domain shifts

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Weakly Supervised Object Detection On 2 | SOTA | HyperAI