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Semi Supervised Object Detection On Coco 5

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mAP

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이 벤치마크에서 각 모델의 성능 결과

모델 이름
mAP
Paper TitleRepository
Adaptive Class-Rebalancing31.35±0.13Semi-Supervised Object Detection with Adaptive Class-Rebalancing Self-Training-
ASTOD30.43Adaptive Self-Training for Object Detection
PseCo32.5PseCo: Pseudo Labeling and Consistency Training for Semi-Supervised Object Detection
Omni-DETR30.2Omni-DETR: Omni-Supervised Object Detection with Transformers
Semi-DETR40.1Semi-DETR: Semi-Supervised Object Detection with Detection Transformers
DETReg24.80±0.2DETReg: Unsupervised Pretraining with Region Priors for Object Detection
MixPL40.1Mixed Pseudo Labels for Semi-Supervised Object Detection
Polishing Teacher32.10±0.15Mind the Gap: Polishing Pseudo labels for Accurate Semi-supervised Object Detection
Revisiting Class Imbalance32.21Revisiting Class Imbalance for End-to-end Semi-Supervised Object Detection-
Dense Teacher33.01Dense Teacher: Dense Pseudo-Labels for Semi-supervised Object Detection
MixTeacher-FCOS33.42MixTeacher: Mining Promising Labels with Mixed Scale Teacher for Semi-Supervised Object Detection
ARSL34.45Ambiguity-Resistant Semi-Supervised Learning for Dense Object Detection
MUM28.52MUM : Mix Image Tiles and UnMix Feature Tiles for Semi-Supervised Object Detection
Unbiased Teacher v231.85±0.09Unbiased Teacher v2: Semi-supervised Object Detection for Anchor-free and Anchor-based Detectors
Unbiased Teacher28.27± 0.11Unbiased Teacher for Semi-Supervised Object Detection
MixTeacher-FRCNN34.06MixTeacher: Mining Promising Labels with Mixed Scale Teacher for Semi-Supervised Object Detection
Efficient Teacher34.11Efficient Teacher: Semi-Supervised Object Detection for YOLOv5
RPL28.4 ± 0.15Rethinking Pseudo Labels for Semi-Supervised Object Detection-
STAC24.38±0.12A Simple Semi-Supervised Learning Framework for Object Detection
VC32.05Semi-supervised Object Detection via Virtual Category Learning
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