Generalized Few-Shot Classification on VOC-MLT

Metric: Average mAP (higher is better)

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#	Model↕	Average mAP▼	Augmentations	Paper	Date↕	Code
1	LMPT(ViT-B/16)	87.88	Yes	LMPT: Prompt Tuning with Class-Specific Embeddin...	2023-05-08	Code
2	CLIP(ViT-B/16)	85.77	Yes	Learning Transferable Visual Models From Natural...	2021-02-26	Code
3	LMPT(ResNet-50)	85.44	Yes	LMPT: Prompt Tuning with Class-Specific Embeddin...	2023-05-08	Code
4	CLIP(ResNet-50)	84.3	Yes	Learning Transferable Visual Models From Natural...	2021-02-26	Code
5	LTML(ResNet-50)	81.44	No	-	-	-
6	PG Loss(ResNet-50)	80.37	No	-	-	-
7	DB Focal(ResNet-50)	78.94	No	Distribution-Balanced Loss for Multi-Label Class...	2020-07-19	Code
8	RS(ResNet-50)	75.38	No	Relay Backpropagation for Effective Learning of ...	2015-12-18	Code
9	CB Focal(ResNet-50)	75.24	No	Class-Balanced Loss Based on Effective Number of...	2019-01-16	Code
10	Focal Loss(ResNet-50)	73.88	No	Focal Loss for Dense Object Detection	2017-08-07	Code
11	OLTR(ResNet-50)	71.02	No	Large-Scale Long-Tailed Recognition in an Open W...	2019-04-10	Code
12	LDAM(ResNet-50)	70.73	No	Learning Imbalanced Datasets with Label-Distribu...	2019-06-18	Code
13	ML-GCN(ResNet-50)	68.92	No	Multi-Label Image Recognition with Graph Convolu...	2019-04-07	Code

#1LMPT(ViT-B/16)SOTA
87.88
Average mAP· Augmentations· 2023-05-08
LMPT: Prompt Tuning with Class-Specific Embedding Loss for Long-tailed Multi-Label Visual Recognition Code
#2CLIP(ViT-B/16)SOTA
85.77
Average mAP· Augmentations· 2021-02-26
Learning Transferable Visual Models From Natural Language Supervision Code
#3LMPT(ResNet-50)
85.44
Average mAP· Augmentations· 2023-05-08
LMPT: Prompt Tuning with Class-Specific Embedding Loss for Long-tailed Multi-Label Visual Recognition Code
#4CLIP(ResNet-50)
84.3
Average mAP· Augmentations· 2021-02-26
Learning Transferable Visual Models From Natural Language Supervision Code
#5LTML(ResNet-50)
81.44
Average mAP
No paper
#6PG Loss(ResNet-50)
80.37
Average mAP
No paper
#7DB Focal(ResNet-50)SOTA
78.94
Average mAP· 2020-07-19
Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets Code
#8RS(ResNet-50)SOTA
75.38
Average mAP· 2015-12-18
Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks Code
#9CB Focal(ResNet-50)
75.24
Average mAP· 2019-01-16
Class-Balanced Loss Based on Effective Number of Samples Code
#10Focal Loss(ResNet-50)
73.88
Average mAP· 2017-08-07
Focal Loss for Dense Object Detection Code
#11OLTR(ResNet-50)
71.02
Average mAP· 2019-04-10
Large-Scale Long-Tailed Recognition in an Open World Code
#12LDAM(ResNet-50)
70.73
Average mAP· 2019-06-18
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Code
#13ML-GCN(ResNet-50)
68.92
Average mAP· 2019-04-07
Multi-Label Image Recognition with Graph Convolutional Networks Code