SOTAVerified

Multi-Label Image Classification

The Multi-Label Image Classification focuses on predicting labels for images in a multi-class classification problem where each image may belong to more than one class.

Papers

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Showing 1–25 of 124 papers

TitleStatusHype
Deep Residual Learning for Image RecognitionCode4
SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth ObservationCode2
Domain Adaptation for Multi-label Image Classification: a Discriminator-free ApproachCode1
Category-Prompt Refined Feature Learning for Long-Tailed Multi-Label Image ClassificationCode1
Multi-Label Plant Species Classification with Self-Supervised Vision TransformersCode1
reBEN: Refined BigEarthNet Dataset for Remote Sensing Image AnalysisCode1
LADI v2: Multi-label Dataset and Classifiers for Low-Altitude Disaster ImageryCode1
Reproducibility Study of CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image ClassificationCode1
TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable PromptCode1
NOAH: Learning Pairwise Object Category Attentions for Image ClassificationCode1
Category-wise Fine-Tuning: Resisting Incorrect Pseudo-Labels in Multi-Label Image Classification with Partial LabelsCode1
Language-Guided Transformer for Federated Multi-Label ClassificationCode1
Feature Guided Masked Autoencoder for Self-supervised Learning in Remote SensingCode1
CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image ClassificationCode1
Semantic-Aware Dual Contrastive Learning for Multi-label Image ClassificationCode1
Category Query Learning for Human-Object Interaction ClassificationCode1
Extending global-local view alignment for self-supervised learning with remote sensing imageryCode1
Causality Compensated Attention for Contextual Biased Visual RecognitionCode1
Discriminator-free Unsupervised Domain Adaptation for Multi-label Image ClassificationCode1
Two-Stream Transformer for Multi-Label Image ClassificationCode1
Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image ClassificationCode1
Self-supervised Learning in Remote Sensing: A ReviewCode1
Boosting Multi-Label Image Classification with Complementary Parallel Self-DistillationCode1
Graph Attention Transformer Network for Multi-Label Image ClassificationCode1
Simple and Robust Loss Design for Multi-Label Learning with Missing LabelsCode1
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All datasetsBigEarthNetBigEarthNet (official test set)MSCOCOBigEarthNet-S1 (official test set)BigEarthNet-10%VizWiz-ClassificationVOC2007

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MoCo-v2 (ResNet50, fine tune)mAP (micro)91.8—Unverified
2MoCo-v3 (ViT-S/16, fine tune)mAP (micro)89.9—Unverified
3MoCo-v2 (ResNet18, fine tune)mAP (micro)89.3—Unverified
4MAE (ViT-S/16, fine tune)mAP (micro)88.9—Unverified
5DINO-MCmAP (micro)88.75—Unverified
6WideResNet-B5-ECAFScore79—Unverified
7ViTM/20FScore77.1—Unverified
8ResNet50FScore76.8—Unverified
9ResNet50mAP (macro)75.36—Unverified
10MLPMixerFScore75.2—Unverified
#ModelMetricClaimedVerifiedStatus
1FG-MAE (ViT-S/16)mAP (micro)89.3—Unverified
2MoCov3 (ViT-S/16)mAP (micro)89.3—Unverified
3MoCov2 (ResNet50)mAP (micro)88.7—Unverified
4MAE (ViT-S/16)mAP (micro)88.6—Unverified
5ViT-S/16mAP (micro)87.8—Unverified
6ResNet50F1 Score76.8—Unverified
#ModelMetricClaimedVerifiedStatus
1IDA-SwinL(H) 384mAP90.3—Unverified
2ML-AGCNmean average precision86.9—Unverified
3IDA-R101(H) 576mAP86.3—Unverified
4IDA-R101(H)mAP84.8—Unverified
#ModelMetricClaimedVerifiedStatus
1FG-MAE (ViT-S/16)mAP (micro)82.7—Unverified
2MAE (ViT-S/16)mAP (micro)81.3—Unverified
3ViT-S/16mAP (micro)79.5—Unverified
#ModelMetricClaimedVerifiedStatus
1DINO-MCmean average precision84.2—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet151Accuracy47.5—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet101MAP96.8—Unverified