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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 124 papers

TitleStatusHype
Estimating Physical Information Consistency of Channel Data Augmentation for Remote Sensing Images—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
ProbMCL: Simple Probabilistic Contrastive Learning for Multi-label Visual ClassificationCode0
MS-Twins: Multi-Scale Deep Self-Attention Networks for Medical Image Segmentation—0
Text as Image: Learning Transferable Adapter for Multi-Label Classification—0
SpliceMix: A Cross-scale and Semantic Blending Augmentation Strategy for Multi-label Image ClassificationCode0
Federated Learning Across Decentralized and Unshared Archives for Remote Sensing Image Classification—0
Conditional Consistency Regularization for Semi-Supervised Multi-label Image Classification—0
PatchCT: Aligning Patch Set and Label Set with Conditional Transport for Multi-Label Image ClassificationCode0
Probability Guided Loss for Long-Tailed Multi-Label Image Classification—0
Pseudo Labels for Single Positive Multi-Label Learning—0
Semantic Embedded Deep Neural Network: A Generic Approach to Boost Multi-Label Image Classification Performance—0
Unsupervised domain adaptation by learning using privileged information—0
Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers—0
Deep Dependency Networks for Multi-Label Classification—0
Multi-label Image Classification using Adaptive Graph Convolutional Networks: from a Single Domain to Multiple Domains—0
Deep Learning based Multi-Label Image Classification of Protest Activities—0
Scene-Aware Label Graph Learning for Multi-Label Image Classification—0
Global Meets Local: Effective Multi-Label Image Classification via Category-Aware Weak Supervision—0
MuMIC -- Multimodal Embedding for Multi-label Image Classification with Tempered Sigmoid—0
G2NetPL: Generic Game-Theoretic Network for Partial-Label Image Classification—0
Multi Label Image Classification using Adaptive Graph Convolutional Networks (ML-AGCN)—0
A Capsule Network for Hierarchical Multi-Label Image Classification—0
Label Structure Preserving Contrastive Embedding for Multi-Label Learning with Missing LabelsCode0
PLMCL: Partial-Label Momentum Curriculum Learning for Multi-Label Image Classification—0
Show:102550
← PrevPage 3 of 5Next →
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