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 101–124 of 124 papers

TitleStatusHype
Visual Attention Consistency Under Image Transforms for Multi-Label Image ClassificationCode0
Multi-View Matrix Completion for Multi-Label Image Classification—0
Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification—0
SoDeep: a Sorting Deep net to learn ranking loss surrogatesCode0
BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding—0
Multi-Label Adversarial Perturbations—0
A Baseline for Multi-Label Image Classification Using An Ensemble of Deep Convolutional Neural NetworksCode0
Multi-Label Zero-Shot Learning with Transfer-Aware Label Embedding Projection—0
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning—0
Structured Label Inference for Visual UnderstandingCode0
Saliency-based Sequential Image Attention with Multiset Prediction—0
Multi-label Image Recognition by Recurrently Discovering Attentional Regions—0
Attribute Recognition by Joint Recurrent Learning of Context and Correlation—0
Joint Learning of Set Cardinality and State Distribution—0
Deep View-Sensitive Pedestrian Attribute Inference in an end-to-end Model—0
Improving Pairwise Ranking for Multi-label Image ClassificationCode0
Learning Spatial Regularization with Image-level Supervisions for Multi-label Image ClassificationCode0
Multi-Label Image Classification with Regional Latent Semantic Dependencies—0
Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization—0
Conditional Graphical Lasso for Multi-Label Image Classification—0
CNN-RNN: A Unified Framework for Multi-label Image ClassificationCode0
Learning Graph Structure for Multi-Label Image Classification via Clique Generation—0
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine—0
Online Learning in The Manifold of Low-Rank Matrices—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