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 ⌀ |
|---|---|---|---|---|---|
10-shot image generation > Semantic Segmentation > 3D Part Segmentation | ShapeNet-Part | PointNet++ (ssg) + JM3D | https://arxiv.org/abs/2308.02982v2 | Class Average IoU | 82.1 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ACDC (Adverse Conditions Dataset with Correspondences) | Segmenter ViT-S/16 | https://arxiv.org/abs/2203.11160v2 | mIoU | 16.7 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-15 | InfoSeg | https://arxiv.org/abs/2110.03477v1 | Pixel Accuracy | 38.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-15 | InMARS | https://arxiv.org/abs/2107.00691v1 | Pixel Accuracy | 31.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-15 | IIC | https://arxiv.org/abs/1807.06653v4 | Pixel Accuracy | 27.7 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-3 | SAN | https://arxiv.org/abs/2211.14513v3 | Pixel Accuracy | 80.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-3 | SGSeg | https://arxiv.org/abs/2210.11810v1 | Pixel Accuracy | 74.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-3 | InfoSeg | https://arxiv.org/abs/2110.03477v1 | Pixel Accuracy | 73.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-3 | InMARS | https://arxiv.org/abs/2107.00691v1 | Pixel Accuracy | 73.1 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-3 | AC | https://arxiv.org/abs/2007.08247v1 | Pixel Accuracy | 72.9 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-3 | IIC | https://arxiv.org/abs/1807.06653v4 | Pixel Accuracy | 72.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-81 | CAUSE-TR (ViT-S/8) | https://arxiv.org/abs/2310.07379v1 | mIoU | 21.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-81 | CAUSE-TR (ViT-S/8) | https://arxiv.org/abs/2310.07379v1 | Pixel Accuracy | 75.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-81 | CAUSE-MLP (ViT-S/8) | https://arxiv.org/abs/2310.07379v1 | mIoU | 19.1 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-81 | CAUSE-MLP (ViT-S/8) | https://arxiv.org/abs/2310.07379v1 | Pixel Accuracy | 78.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-81 | TransFGU (ViT-S/8) | https://arxiv.org/abs/2112.01515v2 | mIoU | 12.7 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-81 | TransFGU (ViT-S/8) | https://arxiv.org/abs/2112.01515v2 | Pixel Accuracy | 64.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-81 | MaskContrast (ResNet-50) | https://arxiv.org/abs/2102.06191v3 | mIoU | 3.7 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-81 | MaskContrast (ResNet-50) | https://arxiv.org/abs/2102.06191v3 | Pixel Accuracy | 8.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | PriMaPs-EM+HP (DINO ViT-B/8) | https://arxiv.org/abs/2404.16818v2 | Accuracy | 83.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | PriMaPs-EM+HP (DINO ViT-B/8) | https://arxiv.org/abs/2404.16818v2 | mIoU | 71.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | EAGLE (DINO, ViT-B/8) | https://arxiv.org/abs/2403.01482v4 | Accuracy | 83.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | EAGLE (DINO, ViT-B/8) | https://arxiv.org/abs/2403.01482v4 | mIoU | 71.1 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | HP | https://arxiv.org/abs/2303.15014v1 | Accuracy | 82.4 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | EQUSS | https://arxiv.org/abs/2312.07342v1 | Accuracy | 82.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | PriMaPs-EM (DINO ViT-B/8) | https://arxiv.org/abs/2404.16818v2 | Accuracy | 80.5 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | PriMaPs-EM (DINO ViT-B/8) | https://arxiv.org/abs/2404.16818v2 | mIoU | 67.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | STEGO | https://arxiv.org/abs/2203.08414v1 | Accuracy | 77.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | IIC | https://arxiv.org/abs/1807.06653v4 | Accuracy | 45.4 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Potsdam-3 | InfoSeg | https://arxiv.org/abs/2110.03477v1 | Pixel Accuracy | 71.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Nighttime Driving | Segmenter ViT-S/16 | https://arxiv.org/abs/2203.11160v2 | mIoU | 18.9 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Dark Zurich | Segmenter ViT-S/16 | https://arxiv.org/abs/2203.11160v2 | mIoU | 14.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Persons | InfoSeg | https://arxiv.org/abs/2110.03477v1 | Pixel Accuracy | 69.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S | PASS | https://arxiv.org/abs/2106.03149v3 | mIoU (val) | 11.5 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S | PASS | https://arxiv.org/abs/2106.03149v3 | mIoU (test) | 11.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | SUIM | DatUS (ViT-B/8) + OC | https://arxiv.org/abs/2401.12820v1 | Pixel Accuracy | 69.98 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | SUIM | DatUS (ViT-B/8) + OC | https://arxiv.org/abs/2401.12820v1 | mIoU | 34.02 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | SUIM | GraPix + AUT | https://doi.org/10.1007/978-3-031-78192-6_13 | Pixel Accuracy | 65.48 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | SUIM | GraPix + AUT | https://doi.org/10.1007/978-3-031-78192-6_13 | mIoU | 30.78 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | SUIM | DatUS (ViT-B/8) | https://arxiv.org/abs/2401.12820v1 | Pixel Accuracy | 64.67 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | SUIM | DatUS (ViT-B/8) | https://arxiv.org/abs/2401.12820v1 | mIoU | 28.48 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | SUIM | GraPix | https://doi.org/10.1007/978-3-031-78192-6_13 | Pixel Accuracy | 64.06 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | SUIM | GraPix | https://doi.org/10.1007/978-3-031-78192-6_13 | mIoU | 28.98 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | PASS (+Saliency map) | https://arxiv.org/abs/2106.03149v3 | mIoU (val) | 43.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | PASS (+Saliency map) | https://arxiv.org/abs/2106.03149v3 | mIoU (test) | 42.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | PASS | https://arxiv.org/abs/2106.03149v3 | mIoU (val) | 32.4 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | PASS | https://arxiv.org/abs/2106.03149v3 | mIoU (test) | 32.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | MaskContrast (+Saliency map) | https://arxiv.org/abs/2102.06191v3 | mIoU (val) | 24.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | MaskContrast (+Saliency map) | https://arxiv.org/abs/2102.06191v3 | mIoU (test) | 24.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | PiCIE (Supervised pretrain) | https://arxiv.org/abs/2103.17070v1 | mIoU (val) | 17.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | PiCIE (Supervised pretrain) | https://arxiv.org/abs/2103.17070v1 | mIoU (test) | 17.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | MDC (Supervised pretrain) | http://arxiv.org/abs/1807.05520v2 | mIoU (val) | 14.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | ImageNet-S-50 | MDC (Supervised pretrain) | http://arxiv.org/abs/1807.05520v2 | mIoU (test) | 14.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | CAUSE (iBOT, ViT-B/16) | https://arxiv.org/abs/2310.07379v1 | Clustering [mIoU] | 53.4 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | CAUSE (ViT-B/8) | https://arxiv.org/abs/2310.07379v1 | Clustering [mIoU] | 53.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | CAUSE (DINOv2, ViT-B/14) | https://arxiv.org/abs/2310.07379v1 | Clustering [mIoU] | 53.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | MaskDistill+CRF | https://arxiv.org/abs/2206.06363v1 | Linear Classifier [mIoU] | 62.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | MaskDistill+CRF | https://arxiv.org/abs/2206.06363v1 | Clustering [mIoU] | 48.9 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | Leopart (ViT-B/8) | https://arxiv.org/abs/2204.13101v2 | Clustering [mIoU] | 47.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | Leopart (ViT-B/8) | https://arxiv.org/abs/2204.13101v2 | FCN [mIoU] | 76.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | HCL (ViT-S/8) | https://www.sciencedirect.com/science/article/pii/S0031320325003735 | Linear Classifier [mIoU] | 75.7 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | HCL (ViT-S/8) | https://www.sciencedirect.com/science/article/pii/S0031320325003735 | Clustering [mIoU] | 46.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | MaskDistill | https://arxiv.org/abs/2206.06363v1 | Linear Classifier [mIoU] | 58.7 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | MaskDistill | https://arxiv.org/abs/2206.06363v1 | Clustering [mIoU] | 45.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | MaskContrast (Saliency) | https://arxiv.org/abs/2102.06191v3 | Linear Classifier [mIoU] | 63.9 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | MaskContrast (Saliency) | https://arxiv.org/abs/2102.06191v3 | Clustering [mIoU] | 44.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | HCL (ViT-S/16) | https://www.sciencedirect.com/science/article/pii/S0031320325003735 | Linear Classifier [mIoU] | 72.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | HCL (ViT-S/16) | https://www.sciencedirect.com/science/article/pii/S0031320325003735 | Clustering [mIoU] | 43.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | Leopart (ViT-S/16) | https://arxiv.org/abs/2204.13101v2 | Linear Classifier [mIoU] | 69.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | Leopart (ViT-S/16) | https://arxiv.org/abs/2204.13101v2 | Clustering [mIoU] | 41.7 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | Leopart (ViT-S/16) | https://arxiv.org/abs/2204.13101v2 | FCN [mIoU] | 71.4 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | MaskContrast | https://arxiv.org/abs/2102.06191v3 | Linear Classifier [mIoU] | 58.4 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | MaskContrast | https://arxiv.org/abs/2102.06191v3 | Clustering [mIoU] | 35.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | SegSort (Edges) | https://arxiv.org/abs/1910.06962v2 | Linear Classifier [mIoU] | 55.86 (KNN) |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | PASCAL VOC 2012 val | SegSort (Edges) | https://arxiv.org/abs/1910.06962v2 | Clustering [mIoU] | - |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-All | DenseSiam | https://arxiv.org/abs/2203.11075v2 | mIoU | 16.4 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes val | Segmenter ViT-S/16 | https://arxiv.org/abs/2203.11160v2 | mIoU | 21.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-171 | CAUSE-TR (ViT-S/8) | https://arxiv.org/abs/2310.07379v1 | mIoU | 15.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-171 | CAUSE-TR (ViT-S/8) | https://arxiv.org/abs/2310.07379v1 | Pixel Accuracy | 46.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-171 | TransFGU (ViT-S/8) | https://arxiv.org/abs/2112.01515v2 | mIoU | 11.93 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-171 | TransFGU (ViT-S/8) | https://arxiv.org/abs/2112.01515v2 | Pixel Accuracy | 34.32 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-171 | PiCIE (ResNet-50) | https://arxiv.org/abs/2103.17070v1 | mIoU | 5.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-171 | PiCIE (ResNet-50) | https://arxiv.org/abs/2103.17070v1 | Pixel Accuracy | 29.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-171 | IIC (ResNet-50) | https://arxiv.org/abs/1807.06653v4 | mIoU | 2.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | COCO-Stuff-171 | IIC (ResNet-50) | https://arxiv.org/abs/1807.06653v4 | Pixel Accuracy | 15.7 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | CUPS | https://arxiv.org/abs/2504.01955v1 | mIoU | 26.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | CUPS | https://arxiv.org/abs/2504.01955v1 | Accuracy | 83.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | ViCE | https://arxiv.org/abs/2111.12460v3 | mIoU | 25.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | ViCE | https://arxiv.org/abs/2111.12460v3 | Accuracy | 84.3 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | EAGLE (DINO, ViT-B/8) | https://arxiv.org/abs/2403.01482v4 | mIoU | 22.1 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | EAGLE (DINO, ViT-B/8) | https://arxiv.org/abs/2403.01482v4 | Accuracy | 79.4 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | EQUSS | https://arxiv.org/abs/2312.07342v1 | mIoU | 22.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | EQUSS | https://arxiv.org/abs/2312.07342v1 | Accuracy | 79.9 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | PriMaPs-EM + STEGO (DINO ViT-B/8) | https://arxiv.org/abs/2404.16818v2 | mIoU | 21.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | PriMaPs-EM + STEGO (DINO ViT-B/8) | https://arxiv.org/abs/2404.16818v2 | Accuracy | 78.6 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | STEGO | https://arxiv.org/abs/2203.08414v1 | mIoU | 21.0 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | STEGO | https://arxiv.org/abs/2203.08414v1 | Accuracy | 73.2 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | EAGLE (DINO, ViT-S/8) | https://arxiv.org/abs/2403.01482v4 | mIoU | 19.7 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | EAGLE (DINO, ViT-S/8) | https://arxiv.org/abs/2403.01482v4 | Accuracy | 81.8 |
10-shot image generation > Semantic Segmentation > Unsupervised Semantic Segmentation | Cityscapes test | PriMaPs-EM (DINO ViT-S/8) | https://arxiv.org/abs/2404.16818v2 | mIoU | 19.4 |
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