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
Showing 11–20 of 124 papers
All datasetsBigEarthNetBigEarthNet (official test set)MSCOCOBigEarthNet-S1 (official test set)BigEarthNet-10%VizWiz-ClassificationVOC2007
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | MoCo-v2 (ResNet50, fine tune) | mAP (micro) | 91.8 | — | Unverified |
| 2 | MoCo-v3 (ViT-S/16, fine tune) | mAP (micro) | 89.9 | — | Unverified |
| 3 | MoCo-v2 (ResNet18, fine tune) | mAP (micro) | 89.3 | — | Unverified |
| 4 | MAE (ViT-S/16, fine tune) | mAP (micro) | 88.9 | — | Unverified |
| 5 | DINO-MC | mAP (micro) | 88.75 | — | Unverified |
| 6 | WideResNet-B5-ECA | FScore | 79 | — | Unverified |
| 7 | ViTM/20 | FScore | 77.1 | — | Unverified |
| 8 | ResNet50 | FScore | 76.8 | — | Unverified |
| 9 | ResNet50 | mAP (macro) | 75.36 | — | Unverified |
| 10 | MLPMixer | FScore | 75.2 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | FG-MAE (ViT-S/16) | mAP (micro) | 89.3 | — | Unverified |
| 2 | MoCov3 (ViT-S/16) | mAP (micro) | 89.3 | — | Unverified |
| 3 | MoCov2 (ResNet50) | mAP (micro) | 88.7 | — | Unverified |
| 4 | MAE (ViT-S/16) | mAP (micro) | 88.6 | — | Unverified |
| 5 | ViT-S/16 | mAP (micro) | 87.8 | — | Unverified |
| 6 | ResNet50 | F1 Score | 76.8 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | IDA-SwinL(H) 384 | mAP | 90.3 | — | Unverified |
| 2 | ML-AGCN | mean average precision | 86.9 | — | Unverified |
| 3 | IDA-R101(H) 576 | mAP | 86.3 | — | Unverified |
| 4 | IDA-R101(H) | mAP | 84.8 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | FG-MAE (ViT-S/16) | mAP (micro) | 82.7 | — | Unverified |
| 2 | MAE (ViT-S/16) | mAP (micro) | 81.3 | — | Unverified |
| 3 | ViT-S/16 | mAP (micro) | 79.5 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | DINO-MC | mean average precision | 84.2 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | ResNet151 | Accuracy | 47.5 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | ResNet101 | MAP | 96.8 | — | Unverified |