Weakly Supervised Object Detection On Pascal 1

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이 벤치마크에서 각 모델의 성능 결과

모델 이름	MAP	Paper Title	Repository
MELM	47.3	Min-Entropy Latent Model for Weakly Supervised Object Detection
Self-Paced Learning	38.11	Self Paced Deep Learning for Weakly Supervised Object Detection
WeakSAM-OICR (with SAM)	58.9	WeakSAM: Segment Anything Meets Weakly-supervised Instance-level Recognition
Pred Net (Ens)	53.6	Dissimilarity Coefficient based Weakly Supervised Object Detection	-
NSOD	38.0	Training Object Detectors from Few Weakly-Labeled and Many Unlabeled Images	-
Ours+FRCNN	52.6	Utilizing the Instability in Weakly Supervised Object Detection	-
Cover + SLSVM	22.7	On learning to localize objects with minimal supervision	-
WSOD2	53.6	WSOD2: Learning Bottom-up and Top-down Objectness Distillation forWeakly-supervised Object Detection	-
SegAgg-Adapt	46.2	Towards automatic visual inspection: A weakly supervised learning method for industrial applicable object detection	-
Ours+PRS	48.8	WSOD with PSNet and Box Regression	-
OICR-Ens + FRCNN	47.0	Multiple Instance Detection Network with Online Instance Classifier Refinement
WS-JDS FRCNN	52.5	Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation
WeakSAM-MIST-Faster RCNN (with SAM)	71.8	WeakSAM: Segment Anything Meets Weakly-supervised Instance-level Recognition
WeakSAM-MIST (with SAM)	67.4	WeakSAM: Segment Anything Meets Weakly-supervised Instance-level Recognition
SegAgg	43.9	Fewer is More: Image Segmentation Based Weakly Supervised Object Detection with Partial Aggregation	-
OIM+IR+FRCNN	52.6	Object Instance Mining for Weakly Supervised Object Detection
PCL-OB-G-Ens + FRCNN	48.8	PCL: Proposal Cluster Learning for Weakly Supervised Object Detection
Our-Ens	54.5	Towards Precise End-to-end Weakly Supervised Object Detection Network
MSLPD	41.7	Few-Example Object Detection with Model Communication
OD-WSCL	56.1	Object Discovery via Contrastive Learning for Weakly Supervised Object Detection

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