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 76–100 of 124 papers

TitleStatusHype
Multi-Label Zero-Shot Learning with Transfer-Aware Label Embedding Projection—0
Deep Dependency Networks for Multi-Label Classification—0
Tensor Composition Net for Visual Relationship Prediction—0
Multi-View Matrix Completion for Multi-Label Image Classification—0
Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification—0
MuMIC -- Multimodal Embedding for Multi-label Image Classification with Tempered Sigmoid—0
Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification—0
Online Learning in The Manifold of Low-Rank Matrices—0
Text as Image: Learning Transferable Adapter for Multi-Label Classification—0
PLMCL: Partial-Label Momentum Curriculum Learning for Multi-Label Image Classification—0
The impact of Compositionality in Zero-shot Multi-label action recognition for Object-based tasks—0
Probability Guided Loss for Long-Tailed Multi-Label Image Classification—0
Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers—0
Pseudo Labels for Single Positive Multi-Label Learning—0
Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning—0
Reconstruction Regularized Deep Metric Learning for Multi-label Image Classification—0
Contrastively Enforcing Distinctiveness for Multi-Label Classification—0
Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes—0
Conditional Graphical Lasso for Multi-Label Image Classification—0
Rethinking Crowdsourcing Annotation: Partial Annotation with Salient Labels for Multi-Label Image Classification—0
A Deep Model for Partial Multi-Label Image Classification with Curriculum Based Disambiguation—0
Saliency-based Sequential Image Attention with Multiset Prediction—0
Scene-Aware Label Graph Learning for Multi-Label Image Classification—0
Unified smoke and fire detection in an evolutionary framework with self-supervised progressive data augment—0
Conditional Consistency Regularization for Semi-Supervised Multi-label Image Classification—0
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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
1MoCov3 (ViT-S/16)mAP (micro)89.3—Unverified
2FG-MAE (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