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 > Domain Generalization | ImageNet-C | Sequencer2D-L | https://arxiv.org/abs/2205.01972v4 | mean Corruption Error (mCE) | 48.9 |
Domain Adaptation > Domain Generalization | ImageNet-C | RVT-S* | https://arxiv.org/abs/2105.07926v4 | mean Corruption Error (mCE) | 49.4 |
Domain Adaptation > Domain Generalization | ImageNet-C | ResNet-50 (PushPull-Conv) + PRIME | https://arxiv.org/abs/2408.04077v2 | mean Corruption Error (mCE) | 49.95 |
Domain Adaptation > Domain Generalization | ImageNet-C | ResNet-50 (PushPull-Conv) + PRIME | https://arxiv.org/abs/2408.04077v2 | Top 1 Accuracy | 69.4 |
Domain Adaptation > Domain Generalization | ImageNet-C | ResNet-50 (PushPull-Conv) + PRIME | https://arxiv.org/abs/2408.04077v2 | Number of params | 25.6 |
Domain Adaptation > Domain Generalization | ImageNet-C | QualNet (ResNet-50) | http://openaccess.thecvf.com//content/CVPR2021/html/Kim_Quality-Agnostic_Image_Recognition_via_Invertible_Decoder_CVPR_2021_paper.html | mean Corruption Error (mCE) | 50.6 |
Domain Adaptation > Domain Generalization | ImageNet-C | PRIME + DeepAugment (ResNet-50) | https://arxiv.org/abs/2112.13547v2 | mean Corruption Error (mCE) | 51.3 |
Domain Adaptation > Domain Generalization | ImageNet-C | PRIME + DeepAugment (ResNet-50) | https://arxiv.org/abs/2112.13547v2 | Top 1 Accuracy | 59.9 |
Domain Adaptation > Domain Generalization | ImageNet-C | GFNet-S | https://arxiv.org/abs/2107.00645v2 | mean Corruption Error (mCE) | 53.8 |
Domain Adaptation > Domain Generalization | ImageNet-C | DINOv2 (ViT-S/14, frozen model, linear eval) | https://arxiv.org/abs/2304.07193v2 | mean Corruption Error (mCE) | 54.4 |
Domain Adaptation > Domain Generalization | ImageNet-C | DINOv2 (ViT-S/14, frozen model, linear eval) | https://arxiv.org/abs/2304.07193v2 | Number of params | 21M |
Domain Adaptation > Domain Generalization | ImageNet-C | PRIME with JSD (ResNet-50) | https://arxiv.org/abs/2112.13547v2 | mean Corruption Error (mCE) | 55.5 |
Domain Adaptation > Domain Generalization | ImageNet-C | PRIME with JSD (ResNet-50) | https://arxiv.org/abs/2112.13547v2 | Top 1 Accuracy | 56.4 |
Domain Adaptation > Domain Generalization | ImageNet-C | RVT-Ti* | https://arxiv.org/abs/2105.07926v4 | mean Corruption Error (mCE) | 57.0 |
Domain Adaptation > Domain Generalization | ImageNet-C | PRIME (ResNet-50) | https://arxiv.org/abs/2112.13547v2 | mean Corruption Error (mCE) | 57.5 |
Domain Adaptation > Domain Generalization | ImageNet-C | PRIME (ResNet-50) | https://arxiv.org/abs/2112.13547v2 | Top 1 Accuracy | 55.0 |
Domain Adaptation > Domain Generalization | ImageNet-C | APR-SP + DeepAugment (ResNet-50) | https://arxiv.org/abs/2108.08487v1 | mean Corruption Error (mCE) | 57.5 |
Domain Adaptation > Domain Generalization | ImageNet-C | DeepAugment (ResNet-50) | https://arxiv.org/abs/2006.16241v3 | mean Corruption Error (mCE) | 60.4 |
Domain Adaptation > Domain Generalization | ImageNet-C | APR-SP (ResNet-50) | https://arxiv.org/abs/2108.08487v1 | mean Corruption Error (mCE) | 65.0 |
Domain Adaptation > Domain Generalization | ImageNet-C | AugMix (ResNet-50) | https://arxiv.org/abs/1912.02781v2 | mean Corruption Error (mCE) | 65.3 |
Domain Adaptation > Domain Generalization | ImageNet-C | Stylized ImageNet (ResNet-50) | https://arxiv.org/abs/1811.12231v3 | mean Corruption Error (mCE) | 69.3 |
Domain Adaptation > Domain Generalization | ImageNet-C | Group-wise Inhibition (ResNet-50) | https://arxiv.org/abs/2103.02152v3 | mean Corruption Error (mCE) | 69.6 |
Domain Adaptation > Domain Generalization | ImageNet-C | ResNet-50 | http://arxiv.org/abs/1903.12261v1 | mean Corruption Error (mCE) | 76.7 |
Domain Adaptation > Domain Generalization | ImageNet-C | DiffAUD (ConvNeXt-Tiny) | https://openaccess.thecvf.com/content/CVPR2024W/NTIRE/html/Daultani_Diffusion-Based_Adaptation_for_Classification_of_Unknown_Degraded_Images_CVPRW_2024_paper.html | Top 1 Accuracy | 64.3 |
Domain Adaptation > Domain Generalization | ImageNet-C | DiffAUD (Swin-Tiny) | https://openaccess.thecvf.com/content/CVPR2024W/NTIRE/html/Daultani_Diffusion-Based_Adaptation_for_Classification_of_Unknown_Degraded_Images_CVPRW_2024_paper.html | Top 1 Accuracy | 61 |
Domain Adaptation > Domain Generalization | ImageNet-C | ViT-B/16-SAM | https://arxiv.org/abs/2106.01548v3 | Top 1 Accuracy | 56.5 |
Domain Adaptation > Domain Generalization | ImageNet-C | ResNet-152x2-SAM | https://arxiv.org/abs/2106.01548v3 | Top 1 Accuracy | 55 |
Domain Adaptation > Domain Generalization | ImageNet-C | DiffAUD (ResNet-50) | https://openaccess.thecvf.com/content/CVPR2024W/NTIRE/html/Daultani_Diffusion-Based_Adaptation_for_Classification_of_Unknown_Degraded_Images_CVPRW_2024_paper.html | Top 1 Accuracy | 52.1 |
Domain Adaptation > Domain Generalization | ImageNet-C | Mixer-B/8-SAM | https://arxiv.org/abs/2106.01548v3 | Top 1 Accuracy | 48.9 |
Domain Adaptation > Domain Generalization | VLCS | CAR-FT (CLIP, ViT-B/16) | https://arxiv.org/abs/2211.16175v1 | Average Accuracy | 85.5 |
Domain Adaptation > Domain Generalization | VLCS | UniDG + CORAL + ConvNeXt-B | https://arxiv.org/abs/2310.10008v1 | Average Accuracy | 84.5 |
Domain Adaptation > Domain Generalization | VLCS | SPG (CLIP, ResNet-50) | https://arxiv.org/abs/2404.19286v2 | Average Accuracy | 84.0 |
Domain Adaptation > Domain Generalization | VLCS | VL2V-SD (CLIP, ViT-B/16) | https://arxiv.org/abs/2310.08255v2 | Average Accuracy | 83.25 |
Domain Adaptation > Domain Generalization | VLCS | MoA (OpenCLIP, ViT-B/16) | https://arxiv.org/abs/2310.11031v2 | Average Accuracy | 83.1 |
Domain Adaptation > Domain Generalization | VLCS | D-Triplet(RegNetY-16GF) | https://arxiv.org/abs/2303.01233v1 | Average Accuracy | 82.9 |
Domain Adaptation > Domain Generalization | VLCS | PromptStyler (CLIP, ViT-B/16) | https://arxiv.org/abs/2307.15199v2 | Average Accuracy | 82.9 |
Domain Adaptation > Domain Generalization | VLCS | SIMPLE+ | https://openreview.net/forum?id=BqrPeZ_e5P | Average Accuracy | 82.7 |
Domain Adaptation > Domain Generalization | VLCS | PromptStyler (CLIP, ViT-L/14) | https://arxiv.org/abs/2307.15199v2 | Average Accuracy | 82.4 |
Domain Adaptation > Domain Generalization | VLCS | GMDG (RegNetY-16GF) | https://arxiv.org/abs/2402.18853v2 | Average Accuracy | 82.4 |
Domain Adaptation > Domain Generalization | VLCS | SPG (CLIP, ViT-B/16) | https://arxiv.org/abs/2404.19286v2 | Average Accuracy | 82.4 |
Domain Adaptation > Domain Generalization | VLCS | PromptStyler (CLIP, ResNet-50) | https://arxiv.org/abs/2307.15199v2 | Average Accuracy | 82.3 |
Domain Adaptation > Domain Generalization | VLCS | SEDGE+ | https://arxiv.org/abs/2203.04600v1 | Average Accuracy | 82.2 |
Domain Adaptation > Domain Generalization | VLCS | CADG | https://arxiv.org/abs/2203.17067v3 | Average Accuracy | 82.2 |
Domain Adaptation > Domain Generalization | VLCS | GMDG (RegNetY-16GF, SWAD) | https://arxiv.org/abs/2402.18853v2 | Average Accuracy | 82.2 |
Domain Adaptation > Domain Generalization | VLCS | MIRO (RegNetY-16GF, SWAD) | https://arxiv.org/abs/2203.10789v2 | Average Accuracy | 81.7 |
Domain Adaptation > Domain Generalization | VLCS | Ensemble of Averages (RegNetY-16GF) | https://arxiv.org/abs/2110.10832v4 | Average Accuracy | 81.1 |
Domain Adaptation > Domain Generalization | VLCS | Ensemble of Averages (ResNeXt-50 32x4d) | https://arxiv.org/abs/2110.10832v4 | Average Accuracy | 80.4 |
Domain Adaptation > Domain Generalization | VLCS | GMoE-S/16 | https://arxiv.org/abs/2206.04046v6 | Average Accuracy | 80.2 |
Domain Adaptation > Domain Generalization | VLCS | SIMPLE | https://openreview.net/forum?id=BqrPeZ_e5P | Average Accuracy | 79.9 |
Domain Adaptation > Domain Generalization | VLCS | SEDGE | https://arxiv.org/abs/2203.04600v1 | Average Accuracy | 79.8 |
Domain Adaptation > Domain Generalization | VLCS | VNE (ResNet-50, SWAD) | https://arxiv.org/abs/2304.01434v1 | Average Accuracy | 79.7 |
Domain Adaptation > Domain Generalization | VLCS | AdaClust (ResNet-50, SWAD) | https://arxiv.org/abs/2112.04766v2 | Average Accuracy | 79.6 |
Domain Adaptation > Domain Generalization | VLCS | MIRO (ResNet-50, SWAD) | https://arxiv.org/abs/2203.10789v2 | Average Accuracy | 79.6 |
Domain Adaptation > Domain Generalization | VLCS | GMDG (ResNet-50, SWAD) | https://arxiv.org/abs/2402.18853v2 | Average Accuracy | 79.6 |
Domain Adaptation > Domain Generalization | VLCS | D-Triplet(Resnet-50) | https://arxiv.org/abs/2303.01233v1 | Average Accuracy | 79.3 |
Domain Adaptation > Domain Generalization | VLCS | POEM | https://arxiv.org/abs/2305.13046v1 | Average Accuracy | 79.2 |
Domain Adaptation > Domain Generalization | VLCS | GMDG (ResNet-50) | https://arxiv.org/abs/2402.18853v2 | Average Accuracy | 79.2 |
Domain Adaptation > Domain Generalization | VLCS | SWAD (ResNet-50) | https://arxiv.org/abs/2102.08604v4 | Average Accuracy | 79.1 |
Domain Adaptation > Domain Generalization | VLCS | Ensemble of Averages (ResNet-50) | https://arxiv.org/abs/2110.10832v4 | Average Accuracy | 79.1 |
Domain Adaptation > Domain Generalization | VLCS | DREAME | https://arxiv.org/abs/2112.09802v3 | Average Accuracy | 79.02 |
Domain Adaptation > Domain Generalization | VLCS | AdaClust (ResNet-50) | https://arxiv.org/abs/2112.04766v2 | Average Accuracy | 78.9 |
Domain Adaptation > Domain Generalization | VLCS | DADG (ResNet-18) | https://arxiv.org/abs/2011.00444v2 | Average Accuracy | 78.21 |
Domain Adaptation > Domain Generalization | VLCS | Fishr (ResNet-50) | https://arxiv.org/abs/2109.02934v3 | Average Accuracy | 78.2 |
Domain Adaptation > Domain Generalization | VLCS | StableNet (ResNet-18) | https://arxiv.org/abs/2104.07876v1 | Average Accuracy | 77.65 |
Domain Adaptation > Domain Generalization | VLCS | RSC (AlexNet) | https://arxiv.org/abs/2007.02454v1 | Average Accuracy | 75.43 |
Domain Adaptation > Domain Generalization | VLCS | DADG (AlexNet) | https://arxiv.org/abs/2011.00444v2 | Average Accuracy | 74.46 |
Domain Adaptation > Domain Generalization | Rotated Fashion-MNIST | MatchDG | https://arxiv.org/abs/2006.07500v3 | Accuracy | 82.8 |
Domain Adaptation > Domain Generalization | Rotated Fashion-MNIST | CSD | https://arxiv.org/abs/2003.12815v2 | Accuracy | 78.9 |
Domain Adaptation > Domain Generalization | Cityscapes to ACDC | ADSI | https://arxiv.org/abs/2504.06781v1 | mIoU | 70.21 |
Domain Adaptation > Domain Generalization | WildDash | ITEN | https://arxiv.org/abs/2107.06235v1 | Mean IoU | 31.2 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | VOLO-D5 | https://arxiv.org/abs/2106.13112v2 | Accuracy - All Images | 57.2 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | VOLO-D5 | https://arxiv.org/abs/2106.13112v2 | Accuracy - Corrupted Images | 51.8 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | VOLO-D5 | https://arxiv.org/abs/2106.13112v2 | Accuracy - Clean Images | 59.7 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ConvNeXt-B | https://arxiv.org/abs/2201.03545v2 | Accuracy - All Images | 53.5 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ConvNeXt-B | https://arxiv.org/abs/2201.03545v2 | Accuracy - Corrupted Images | 46.9 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ConvNeXt-B | https://arxiv.org/abs/2201.03545v2 | Accuracy - Clean Images | 56 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ResNeXt-101 32x16d | http://arxiv.org/abs/1611.05431v2 | Accuracy - All Images | 51.7 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ResNeXt-101 32x16d | http://arxiv.org/abs/1611.05431v2 | Accuracy - Corrupted Images | 48.1 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ResNeXt-101 32x16d | http://arxiv.org/abs/1611.05431v2 | Accuracy - Clean Images | 54.8 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B8 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - All Images | 50.5 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B8 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Corrupted Images | 45.8 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B8 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Clean Images | 53.2 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B7 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - All Images | 49.7 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B7 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Corrupted Images | 45 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B7 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Clean Images | 52 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B6 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - All Images | 49.6 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B6 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Corrupted Images | 44.7 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B6 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Clean Images | 53.2 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B5 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - All Images | 49.1 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B5 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Corrupted Images | 44 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B5 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Clean Images | 51.7 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ViT-16/L-224 | https://arxiv.org/abs/2010.11929v2 | Accuracy - All Images | 49 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ResNet-50 (gn) | https://arxiv.org/abs/2110.00476v1 | Accuracy - All Images | 48.9 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ResNet-50 (gn) | https://arxiv.org/abs/2110.00476v1 | Accuracy - Corrupted Images | 39.1 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ResNet-50 (gn) | https://arxiv.org/abs/2110.00476v1 | Accuracy - Clean Images | 44.4 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B4 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - All Images | 48.1 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B4 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Corrupted Images | 42.5 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | EfficientNet-B4 (advprop+autoaug) | https://arxiv.org/abs/1911.09665v2 | Accuracy - Clean Images | 51.4 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ResNet-152 | http://arxiv.org/abs/1512.03385v1 | Accuracy - All Images | 47.5 |
Domain Adaptation > Domain Generalization | VizWiz-Classification | ResNet-152 | http://arxiv.org/abs/1512.03385v1 | Accuracy - Corrupted Images | 43.3 |
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