Domain Adaptation
Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.
Further readings:
( Image credit: Unsupervised Image-to-Image Translation Networks )
Papers
Showing 551–575 of 6439 papers
All datasetsOffice-31SYNTHIA-to-CityscapesGTA5 to CityscapesOffice-HomeVisDA2017ImageCLEF-DACityscapes to ACDCMNIST-to-USPSSVHN-to-MNISTUSPS-to-MNISTSVNH-to-MNISTMoLane
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | FFTAT | Average Accuracy | 96 | — | Unverified |
| 2 | PMTrans | Average Accuracy | 95.3 | — | Unverified |
| 3 | CMKD | Average Accuracy | 94.4 | — | Unverified |
| 4 | SSRT-B (ours) | Average Accuracy | 93.5 | — | Unverified |
| 5 | CDTrans | Average Accuracy | 92.6 | — | Unverified |
| 6 | CoVi | Average Accuracy | 91.8 | — | Unverified |
| 7 | GSDE | Average Accuracy | 91.7 | — | Unverified |
| 8 | FixBi | Average Accuracy | 91.4 | — | Unverified |
| 9 | Contrastive Adaptation Network | Average Accuracy | 90.6 | — | Unverified |
| 10 | BIWAA | Average Accuracy | 90.5 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | HALO | mIoU | 78.1 | — | Unverified |
| 2 | ILM-ASSL | mIoU | 76.6 | — | Unverified |
| 3 | DCF | mIoU | 69.3 | — | Unverified |
| 4 | HRDA+PiPa | mIoU | 68.2 | — | Unverified |
| 5 | MIC | mIoU | 67.3 | — | Unverified |
| 6 | FREDOM - Transformer | mIoU | 67 | — | Unverified |
| 7 | HRDA | mIoU | 65.8 | — | Unverified |
| 8 | SePiCo | mIoU | 64.3 | — | Unverified |
| 9 | MIC + Guidance Training | mIoU | 63.8 | — | Unverified |
| 10 | DAFormer + ProCST | mIoU | 61.6 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | HALO | mIoU | 77.8 | — | Unverified |
| 2 | DCF | mIoU | 77.7 | — | Unverified |
| 3 | ILM-ASSL | mIoU | 76.1 | — | Unverified |
| 4 | MIC | mIoU | 75.9 | — | Unverified |
| 5 | HRDA+PiPa | mIoU | 75.6 | — | Unverified |
| 6 | HRDA | mIoU | 73.8 | — | Unverified |
| 7 | FREDOM - Transformer | mIoU | 73.6 | — | Unverified |
| 8 | HALO | mIoU | 73.3 | — | Unverified |
| 9 | SePiCo | mIoU | 70.3 | — | Unverified |
| 10 | DAFormer + ProCST | mIoU | 69.4 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SWG | Accuracy | 92.3 | — | Unverified |
| 2 | RCL | Accuracy | 90 | — | Unverified |
| 3 | PGA (ViT-L/14) | Accuracy | 89.4 | — | Unverified |
| 4 | PMTrans | Accuracy | 89 | — | Unverified |
| 5 | CMKD | Accuracy | 89 | — | Unverified |
| 6 | MIC | Accuracy | 86.2 | — | Unverified |
| 7 | PGA (ViT-B/16) | Accuracy | 85.1 | — | Unverified |
| 8 | ELS | Accuracy | 84.6 | — | Unverified |
| 9 | SDAT (ViT-B/16) | Accuracy | 84.3 | — | Unverified |
| 10 | CDTrans (DeiT-B) | Accuracy | 80.5 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | FFTAT | Accuracy | 93.8 | — | Unverified |
| 2 | RCL | Accuracy | 93.2 | — | Unverified |
| 3 | MIC | Accuracy | 92.8 | — | Unverified |
| 4 | SWG | Accuracy | 92.7 | — | Unverified |
| 5 | CMKD | Accuracy | 91.8 | — | Unverified |
| 6 | DePT | Accuracy | 90.7 | — | Unverified |
| 7 | SDAT(ViT) | Accuracy | 89.8 | — | Unverified |
| 8 | SFDA2++ | Accuracy | 89.6 | — | Unverified |
| 9 | PMtrans | Accuracy | 88.8 | — | Unverified |
| 10 | CoVi | Accuracy | 88.5 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | CMKD | Accuracy | 94.3 | — | Unverified |
| 2 | MCC+NWD | Accuracy | 90.7 | — | Unverified |
| 3 | GLOT-DR | Accuracy | 90.4 | — | Unverified |
| 4 | SPL | Accuracy | 90.3 | — | Unverified |
| 5 | DFA-SAFN | Accuracy | 90.2 | — | Unverified |
| 6 | DADA | Accuracy | 89.3 | — | Unverified |
| 7 | DFA-ENT | Accuracy | 89.1 | — | Unverified |
| 8 | MEDM | Accuracy | 88.9 | — | Unverified |
| 9 | DDA | Accuracy | 88.9 | — | Unverified |
| 10 | IAFN+ENT | Accuracy | 88.9 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SoRA | mIoU | 78.8 | — | Unverified |
| 2 | Rein | mIoU | 77.6 | — | Unverified |
| 3 | CoDA | mIoU | 72.6 | — | Unverified |
| 4 | Refign (HRDA) | mIoU | 72.1 | — | Unverified |
| 5 | HALO | mIoU | 71.9 | — | Unverified |
| 6 | MIC | mIoU | 70.4 | — | Unverified |
| 7 | HRDA | mIoU | 68 | — | Unverified |
| 8 | Refign (DAFormer) | mIoU | 65.5 | — | Unverified |
| 9 | VBLC (DAFormer) | mIoU | 64.2 | — | Unverified |
| 10 | CMFormer | mIoU | 60.1 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | FACT | Accuracy | 98.8 | — | Unverified |
| 2 | FAMCD | Accuracy | 98.72 | — | Unverified |
| 3 | DFA-MCD | Accuracy | 98.6 | — | Unverified |
| 4 | Mean teacher | Accuracy | 98.26 | — | Unverified |
| 5 | DRANet | Accuracy | 98.2 | — | Unverified |
| 6 | SHOT | Accuracy | 98 | — | Unverified |
| 7 | DFA-ENT | Accuracy | 97.9 | — | Unverified |
| 8 | CyCleGAN (Light-weight Calibrator) | Accuracy | 97.1 | — | Unverified |