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SOTA
Multi-Label Classification
Multi Label Classification On Ms Coco
Multi Label Classification On Ms Coco
Metrics
mAP
Results
Performance results of various models on this benchmark
Columns
Model Name
mAP
Paper Title
ADDS(ViT-L-336, resolution 1344)
93.54
Open Vocabulary Multi-Label Classification with Dual-Modal Decoder on Aligned Visual-Textual Features
ADDS(ViT-L-336, resolution 640)
93.41
Open Vocabulary Multi-Label Classification with Dual-Modal Decoder on Aligned Visual-Textual Features
ADDS(ViT-L-336, resolution 336)
91.76
Open Vocabulary Multi-Label Classification with Dual-Modal Decoder on Aligned Visual-Textual Features
ML-Decoder(TResNet-XL, resolution 640)
91.4
ML-Decoder: Scalable and Versatile Classification Head
Q2L-CvT(ImageNet-21K pretraining, resolution 384)
91.3
Query2Label: A Simple Transformer Way to Multi-Label Classification
MLD-TResNet-L-AAM[640x640]
91.30
Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image Classification
ML-Decoder(TResNet-L, resolution 640)
91.1
ML-Decoder: Scalable and Versatile Classification Head
Q2L-SwinL(ImageNet-21K pretraining, resolution 384)
90.5
Query2Label: A Simple Transformer Way to Multi-Label Classification
IDA-SwinL
90.3
Causality Compensated Attention for Contextual Biased Visual Recognition
CCD-SwinL
90.3
Contextual Debiasing for Visual Recognition With Causal Mechanisms
Q2L-TResL(ImageNet-21K pretraining, resolution 640)
90.3
Query2Label: A Simple Transformer Way to Multi-Label Classification
MlTr-XL(ImageNet-21K pretraining, resolution 384)
90.0
MlTr: Multi-label Classification with Transformer
TResNet-L-V2, (ImageNet-21K-P pretraining, resolution 640)
89.8
ImageNet-21K Pretraining for the Masses
MlTr-L(ImageNet-21K pretraining, resolution 384)
88.5
MlTr: Multi-label Classification with Transformer
TResNet-XL (resolution 640)
88.4
Asymmetric Loss For Multi-Label Classification
TResNet-L-V2, (ImageNet-21K-P pretraining, resolution 448)
88.4
ImageNet-21K Pretraining for the Masses
GKGNet(resolution 576)
87.7
GKGNet: Group K-Nearest Neighbor based Graph Convolutional Network for Multi-Label Image Recognition
M3TR(ImageNet-21K-P pretraining, resolution 448)
87.5
M3TR: Multi-modal Multi-label Recognition with Transformer
GKGNet(resolution 448)
86.7
GKGNet: Group K-Nearest Neighbor based Graph Convolutional Network for Multi-Label Image Recognition
TResNet-L (resolution 448)
86.6
Asymmetric Loss For Multi-Label Classification
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Multi Label Classification On Ms Coco | SOTA | HyperAI