task_path stringlengths 3 199 ⌀ | dataset stringlengths 1 128 ⌀ | model_name stringlengths 1 223 ⌀ | paper_url stringlengths 21 601 ⌀ | metric_name stringlengths 1 50 ⌀ | metric_value stringlengths 1 9.22k ⌀ |
|---|---|---|---|---|---|
Domain Adaptation | SYNTHIA-to-Cityscapes | CorDA (ResNet-101) | https://arxiv.org/abs/2104.13613v2 | mIoU | 55.0 |
Domain Adaptation | SYNTHIA-to-Cityscapes | SAC (ResNet-101) | https://arxiv.org/abs/2105.00097v1 | mIoU | 52.6 |
Domain Adaptation | SYNTHIA-to-Cityscapes | STPL | https://arxiv.org/abs/2303.14361v1 | mIoU | 51.8 |
Domain Adaptation | SYNTHIA-to-Cityscapes | RPT (ResNet-101) | https://arxiv.org/abs/2006.06570v1 | mIoU | 51.2 |
Domain Adaptation | SYNTHIA-to-Cityscapes | IAST (ResNet-101) | https://arxiv.org/abs/2008.12197v1 | mIoU | 49.8 |
Domain Adaptation | SYNTHIA-to-Cityscapes | SAC (VGG-16) | https://arxiv.org/abs/2105.00097v1 | mIoU | 49.1 |
Domain Adaptation | SYNTHIA-to-Cityscapes | PyCDA (ResNet-101) | https://arxiv.org/abs/1908.09547v1 | mIoU | 46.7 |
Domain Adaptation | SYNTHIA-to-Cityscapes | BiMaL | https://arxiv.org/abs/2108.03267v1 | mIoU | 46.2 |
Domain Adaptation | SYNTHIA-to-Cityscapes | FADA (ResNet-101) | https://arxiv.org/abs/2007.09222v1 | mIoU | 45.2 |
Domain Adaptation | SYNTHIA-to-Cityscapes | PIT (ResNet-101) | http://openaccess.thecvf.com/content_CVPR_2020/html/Lv_Cross-Domain_Semantic_Segmentation_via_Domain-Invariant_Interactive_Relation_Transfer_CVPR_2020_paper.html | mIoU | 44.0 |
Domain Adaptation | SYNTHIA-to-Cityscapes | SA-I2I (VGG-16) | https://arxiv.org/abs/2009.01166v1 | mIoU | 41.5 |
Domain Adaptation | SYNTHIA-to-Cityscapes | ADVENT (ResNet-101) | http://arxiv.org/abs/1811.12833v2 | mIoU | 41.2 |
Domain Adaptation | SYNTHIA-to-Cityscapes | LDR (VGG-16) | https://arxiv.org/abs/2003.04614v3 | mIoU | 41.1 |
Domain Adaptation | SYNTHIA-to-Cityscapes | CD-AM (VGG-16) | https://arxiv.org/abs/2003.04010v1 | mIoU | 40.8 |
Domain Adaptation | SYNTHIA-to-Cityscapes | FDA (VGG-16) | https://arxiv.org/abs/2004.05498v1 | mIoU | 40.5 |
Domain Adaptation | SYNTHIA-to-Cityscapes | FADA (VGG-16) | https://arxiv.org/abs/2007.09222v1 | mIoU | 39.5 |
Domain Adaptation | SYNTHIA-to-Cityscapes | PIT (VGG-16) | http://openaccess.thecvf.com/content_CVPR_2020/html/Lv_Cross-Domain_Semantic_Segmentation_via_Domain-Invariant_Interactive_Relation_Transfer_CVPR_2020_paper.html | mIoU | 38.1 |
Domain Adaptation | SYNTHIA-to-Cityscapes | PyCDA (VGG-16) | https://arxiv.org/abs/1908.09547v1 | mIoU | 35.9 |
Domain Adaptation | Sim10k | MILA | https://arxiv.org/abs/2309.01086v1 | mAP | 57.4 |
Domain Adaptation | Synscapes-to-Cityscapes | ProDA+CRA | https://arxiv.org/abs/2109.06422v2 | mIoU | 60.2 |
Domain Adaptation | Synscapes-to-Cityscapes | IntraDA | https://arxiv.org/abs/2004.07703v4 | mIoU | 54.2 |
Domain Adaptation | Synscapes-to-Cityscapes | AdaptSegNet | https://arxiv.org/abs/1802.10349v3 | mIoU | 52.7 |
Domain Adaptation | MuLane | UFLD-SGADA-ResNet32 | https://arxiv.org/abs/2206.08083v4 | Lane Accuracy (LA) | 91.63 |
Domain Adaptation | MuLane | UFLD-SGPCS-ResNet18 | https://arxiv.org/abs/2206.08083v4 | Lane Accuracy (LA) | 91.57 |
Domain Adaptation | MuLane | UFLD-SGPCS-ResNet32 | https://arxiv.org/abs/2206.08083v4 | Lane Accuracy (LA) | 91.55 |
Domain Adaptation | MuLane | UFLD-SGADA-ResNet18 | https://arxiv.org/abs/2206.08083v4 | Lane Accuracy (LA) | 90.71 |
Domain Adaptation | MuLane | UFLD-ADDA-ResNet32 | https://arxiv.org/abs/2206.08083v4 | Lane Accuracy (LA) | 90.22 |
Domain Adaptation | MuLane | UFLD-ADDA-ResNet18 | https://arxiv.org/abs/2206.08083v4 | Lane Accuracy (LA) | 89.83 |
Domain Adaptation | MuLane | UFLD-DANN-ResNet32 | https://arxiv.org/abs/2206.08083v4 | Lane Accuracy (LA) | 88.76 |
Domain Adaptation | MuLane | UFLD-DANN-ResNet18 | https://arxiv.org/abs/2206.08083v4 | Lane Accuracy (LA) | 86.01 |
Domain Adaptation | Noisy-SYND-to-MNIST | Butterfly | https://arxiv.org/abs/1905.07720v3 | Average Accuracy | 94.09 |
Domain Adaptation | HMDB --> UCF (full) | TranSVAE | null | Accuracy | 98.95 |
Domain Adaptation | HMDB --> UCF (full) | UNITE | https://arxiv.org/abs/2312.02914v4 | Accuracy | 92.5 |
Domain Adaptation | HMDB --> UCF (full) | ABG | https://arxiv.org/abs/2007.15829v1 | Accuracy | 85.11 |
Domain Adaptation | HMDB --> UCF (full) | TA3N | https://arxiv.org/abs/1907.12743v6 | Accuracy | 81.79 |
Domain Adaptation | SYNTHIA-to-Cityscapes Labels | MRNet | https://arxiv.org/abs/1912.11164v3 | mIoU | 46.5 |
Domain Adaptation | USPS-to-MNIST | FAMCD | https://doi.org/10.1117/12.2646422 | Accuracy | 98.75 |
Domain Adaptation | USPS-to-MNIST | FACT | https://arxiv.org/abs/2306.00607v2 | Accuracy | 98.6 |
Domain Adaptation | USPS-to-MNIST | SHOT | https://arxiv.org/abs/2002.08546v6 | Accuracy | 98.4 |
Domain Adaptation | USPS-to-MNIST | CyCleGAN (Light-weight Calibrator) | https://arxiv.org/abs/1911.12796v2 | Accuracy | 98.3 |
Domain Adaptation | USPS-to-MNIST | 3CATN | https://arxiv.org/abs/1909.07618v1 | Accuracy | 98.3 |
Domain Adaptation | USPS-to-MNIST | Mean teacher | http://arxiv.org/abs/1706.05208v4 | Accuracy | 98.07 |
Domain Adaptation | USPS-to-MNIST | CDAN | http://arxiv.org/abs/1705.10667v4 | Accuracy | 98.0 |
Domain Adaptation | USPS-to-MNIST | DRANet | https://arxiv.org/abs/2103.13447v2 | Accuracy | 97.8 |
Domain Adaptation | USPS-to-MNIST | DFA-MCD | https://arxiv.org/abs/2006.12770v5 | Accuracy | 96.6 |
Domain Adaptation | USPS-to-MNIST | DeepJDOT | http://arxiv.org/abs/1803.10081v3 | Accuracy | 96.4 |
Domain Adaptation | USPS-to-MNIST | MCD+CAT | https://arxiv.org/abs/1903.09980v2 | Accuracy | 96.3 |
Domain Adaptation | USPS-to-MNIST | DFA-ENT | https://arxiv.org/abs/2006.12770v5 | Accuracy | 96.2 |
Domain Adaptation | USPS-to-MNIST | MCD | http://arxiv.org/abs/1712.02560v4 | Accuracy | 95.7 |
Domain Adaptation | USPS-to-MNIST | SRDA (RAN) | https://arxiv.org/abs/1905.10748v4 | Accuracy | 95.03 |
Domain Adaptation | SVHN-to-MNIST | Mean teacher | http://arxiv.org/abs/1706.05208v4 | Accuracy | 99.18 |
Domain Adaptation | SVHN-to-MNIST | SHOT | https://arxiv.org/abs/2002.08546v6 | Accuracy | 98.9 |
Domain Adaptation | SVHN-to-MNIST | DFA-MCD | https://arxiv.org/abs/2006.12770v5 | Accuracy | 98.9 |
Domain Adaptation | SVHN-to-MNIST | FAMCD | https://doi.org/10.1117/12.2646422 | Accuracy | 98.76 |
Domain Adaptation | SVHN-to-MNIST | DFA-ENT | https://arxiv.org/abs/2006.12770v5 | Accuracy | 98.2 |
Domain Adaptation | SVHN-to-MNIST | CyCleGAN (Light-weight Calibrator) | https://arxiv.org/abs/1911.12796v2 | Accuracy | 97.5 |
Domain Adaptation | SVHN-to-MNIST | MCD | http://arxiv.org/abs/1712.02560v4 | Accuracy | 95.8 |
Domain Adaptation | SVHN-to-MNIST | PFA | https://arxiv.org/abs/1811.08585v2 | Accuracy | 93.9 |
Domain Adaptation | SVHN-to-MNIST | MSTN | https://icml.cc/Conferences/2018/Schedule?showEvent=1961 | Accuracy | 93.3 |
Domain Adaptation | SVHN-to-MNIST | FACT | https://arxiv.org/abs/2306.00607v2 | Accuracy | 90.6 |
Domain Adaptation | SVHN-to-MNIST | CYCADA | http://arxiv.org/abs/1711.03213v3 | Accuracy | 90.4 |
Domain Adaptation | SVHN-to-MNIST | CDAN | http://arxiv.org/abs/1705.10667v4 | Accuracy | 89.2 |
Domain Adaptation | SVHN-to-MNIST | ADDN | http://arxiv.org/abs/1702.05464v1 | Accuracy | 80.1 |
Domain Adaptation | SVHN-to-MNIST | SBADA | http://arxiv.org/abs/1705.08824v2 | Accuracy | 76.1 |
Domain Adaptation | Panoptic SYNTHIA-to-Mapillary | MC-PanDA | https://arxiv.org/abs/2407.14110v1 | mPQ | 38.7 |
Domain Adaptation | Panoptic SYNTHIA-to-Mapillary | EDAPS | https://arxiv.org/abs/2304.14291v2 | mPQ | 36.6 |
Domain Adaptation | Panoptic SYNTHIA-to-Mapillary | CVRN | https://arxiv.org/abs/2103.02584v1 | mPQ | 21.3 |
Domain Adaptation | Panoptic SYNTHIA-to-Mapillary | FDA | https://arxiv.org/abs/2004.05498v1 | mPQ | 19.1 |
Domain Adaptation | Panoptic SYNTHIA-to-Mapillary | ADVENT | http://arxiv.org/abs/1811.12833v2 | mPQ | 18.3 |
Domain Adaptation | Olympic-to-HMDBsmall | TA3N | https://arxiv.org/abs/1905.10861v5 | Accuracy | 92.92 |
Domain Adaptation | Olympic-to-HMDBsmall | TemPooling + RevGrad | http://arxiv.org/abs/1409.7495v2 | Accuracy | 90.00 |
Domain Adaptation | Olympic-to-HMDBsmall | W. Sultani et al. | http://openaccess.thecvf.com/content_cvpr_2014/html/Sultani_Human_Action_Recognition_2014_CVPR_paper.html | Accuracy | 47.91 |
Domain Adaptation | GTA5+Synscapes to Cityscapes | MSCL | https://arxiv.org/abs/2103.04717v3 | mIoU | 59.0 |
Domain Adaptation | GTA5+Synscapes to Cityscapes | MADAN | https://arxiv.org/abs/1910.12181v1 | mIoU | 55.7 |
Domain Adaptation | GTA5+Synscapes to Cityscapes | MDAN | http://papers.nips.cc/paper/8075-adversarial-multiple-source-domain-adaptation | mIoU | 55.2 |
Domain Adaptation | GTA5+Synscapes to Cityscapes | MRNet + Adaboost | https://arxiv.org/abs/2103.15685v3 | mIoU | 50.8 |
Domain Adaptation | GTA5+Synscapes to Cityscapes | MRNet | https://arxiv.org/abs/1912.11164v3 | mIoU | 47.6 |
Domain Adaptation | MNIST-M-to-MNIST | DRANet | https://arxiv.org/abs/2103.13447v2 | Accuracy | 99.3 |
Domain Adaptation | Noisy-MNIST-to-SYND | Butterfly | https://arxiv.org/abs/1905.07720v3 | Average Accuracy | 57.55 |
Domain Adaptation | Nikon RAW Low Light | FSDA-LL Sony -> Nikon | https://arxiv.org/abs/2303.15528v1 | PSNR | 30.3 |
Domain Adaptation | Nikon RAW Low Light | FSDA-LL Sony -> Nikon | https://arxiv.org/abs/2303.15528v1 | SSIM | 0.913 |
Domain Adaptation | Rotating MNIST | PCIDA | https://arxiv.org/abs/2007.01807v2 | Accuracy (%) | 87.1% |
Domain Adaptation | Rotating MNIST | CIDA | https://arxiv.org/abs/2007.01807v2 | Accuracy (%) | 85.7% |
Domain Adaptation | Office-31 | FFTAT | https://arxiv.org/abs/2411.07794v1 | Average Accuracy | 96.0 |
Domain Adaptation | Office-31 | PMTrans | https://arxiv.org/abs/2303.13434v2 | Average Accuracy | 95.3 |
Domain Adaptation | Office-31 | CMKD | https://ieeexplore.ieee.org/document/10505301 | Average Accuracy | 94.4 |
Domain Adaptation | Office-31 | SSRT-B (ours) | https://arxiv.org/abs/2204.07683v1 | Average Accuracy | 93.5 |
Domain Adaptation | Office-31 | CDTrans | https://arxiv.org/abs/2109.06165v4 | Average Accuracy | 92.6 |
Domain Adaptation | Office-31 | CoVi | https://arxiv.org/abs/2111.13353v3 | Average Accuracy | 91.8 |
Domain Adaptation | Office-31 | GSDE | https://arxiv.org/abs/2311.09599v1 | Average Accuracy | 91.7 |
Domain Adaptation | Office-31 | FixBi | https://arxiv.org/abs/2011.09230v2 | Average Accuracy | 91.4 |
Domain Adaptation | Office-31 | Contrastive Adaptation Network | http://arxiv.org/abs/1901.00976v2 | Average Accuracy | 90.6 |
Domain Adaptation | Office-31 | BIWAA | https://openaccess.thecvf.com/content/WACV2023/html/Westfechtel_Backprop_Induced_Feature_Weighting_for_Adversarial_Domain_Adaptation_With_Iterative_WACV_2023_paper.html | Average Accuracy | 90.5 |
Domain Adaptation | Office-31 | DALN | https://arxiv.org/abs/2204.03838v1 | Average Accuracy | 90.4 |
Domain Adaptation | Office-31 | ELS | https://arxiv.org/abs/2302.00194v1 | Average Accuracy | 90.4 |
Domain Adaptation | Office-31 | dSNE | http://openaccess.thecvf.com/content_CVPR_2019/html/Xu_d-SNE_Domain_Adaptation_Using_Stochastic_Neighborhood_Embedding_CVPR_2019_paper.html | Average Accuracy | 90.01 |
Domain Adaptation | Office-31 | ASAN | https://link.springer.com/chapter/10.1007/978-3-030-69535-4_28 | Average Accuracy | 90.0 |
Domain Adaptation | Office-31 | CPGA | https://arxiv.org/abs/2106.15326v1 | Average Accuracy | 89.9 |
Domain Adaptation | Office-31 | SFDA2 | https://arxiv.org/abs/2403.10834v1 | Average Accuracy | 89.9 |
Domain Adaptation | Office-31 | MDAIR | http://arxiv.org/abs/1904.02322v2 | Average Accuracy | 89.8 |
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