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 ⌀ |
|---|---|---|---|---|---|
Image Segmentation | RMAS | MASNet | https://ieeexplore.ieee.org/document/10113781 | mIoU | 0.731 |
Image Segmentation | RMAS | MASNet | https://ieeexplore.ieee.org/document/10113781 | E-measure | 0.920 |
Image Segmentation | RMAS | MASNet | https://ieeexplore.ieee.org/document/10113781 | MAE | 0.024 |
Image Segmentation | RMAS | ZoomNet | https://arxiv.org/abs/2203.02688v1 | S-measure | 0.855 |
Image Segmentation | RMAS | ZoomNet | https://arxiv.org/abs/2203.02688v1 | mIoU | 0.728 |
Image Segmentation | RMAS | ZoomNet | https://arxiv.org/abs/2203.02688v1 | E-measure | 0.915 |
Image Segmentation | RMAS | ZoomNet | https://arxiv.org/abs/2203.02688v1 | MAE | 0.022 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | SAM2-UNet | https://arxiv.org/abs/2408.08870v1 | MAE | 0.022 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | SAM2-UNet | https://arxiv.org/abs/2408.08870v1 | IoU | 0.918 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | SAM2-UNet | https://arxiv.org/abs/2408.08870v1 | F-measure | 0.957 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | HetNet | https://arxiv.org/abs/2211.15644v1 | MAE | 0.043 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | HetNet | https://arxiv.org/abs/2211.15644v1 | IoU | 0.828 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | HetNet | https://arxiv.org/abs/2211.15644v1 | F-measure | 0.906 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | PMD | http://openaccess.thecvf.com/content_CVPR_2020/html/Lin_Progressive_Mirror_Detection_CVPR_2020_paper.html | MAE | 0.047 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | PMD | http://openaccess.thecvf.com/content_CVPR_2020/html/Lin_Progressive_Mirror_Detection_CVPR_2020_paper.html | IoU | 0.815 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | PMD | http://openaccess.thecvf.com/content_CVPR_2020/html/Lin_Progressive_Mirror_Detection_CVPR_2020_paper.html | F-measure | 0.892 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | SANet | http://openaccess.thecvf.com//content/CVPR2022/html/Guan_Learning_Semantic_Associations_for_Mirror_Detection_CVPR_2022_paper.html | MAE | 0.054 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | SANet | http://openaccess.thecvf.com//content/CVPR2022/html/Guan_Learning_Semantic_Associations_for_Mirror_Detection_CVPR_2022_paper.html | IoU | 0.798 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | SANet | http://openaccess.thecvf.com//content/CVPR2022/html/Guan_Learning_Semantic_Associations_for_Mirror_Detection_CVPR_2022_paper.html | F-measure | 0.877 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | MirrorNet | https://arxiv.org/abs/1908.09101v2 | MAE | 0.065 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | MirrorNet | https://arxiv.org/abs/1908.09101v2 | IoU | 0.790 |
Image Segmentation | MSD (Mirror Segmentation Dataset) | MirrorNet | https://arxiv.org/abs/1908.09101v2 | F-measure | 0.857 |
Image Segmentation | PASCAL VOC | OneNete,4-C | https://arxiv.org/abs/2411.09838v1 | mIoU | 63.6 |
Image Segmentation | PASCAL VOC | OneNeted,4 | https://arxiv.org/abs/2411.09838v1 | mIoU | 14.9 |
Image Segmentation | PASCAL VOC | OneNete,4-S | https://arxiv.org/abs/2411.09838v1 | mAP0.5 | 52.75 |
Image Segmentation | Pascal Panoptic Parts | HIPIE (ViT-H) | https://arxiv.org/abs/2307.00764v2 | mIoUPartS | 63.8 |
Image Segmentation | Pascal Panoptic Parts | PPS | https://arxiv.org/abs/2106.06351v1 | mIoUPartS | 58.6 |
Image Segmentation | Pascal Panoptic Parts | HIPIE (ResNet-50) | https://arxiv.org/abs/2307.00764v2 | mIoUPartS | 57.2 |
Image Segmentation | Pascal Panoptic Parts | JPPF | https://arxiv.org/abs/2212.07671v2 | mIoUPartS | 54.4 |
Image Segmentation | PMD | SAM2-UNet | https://arxiv.org/abs/2408.08870v1 | MAE | 0.027 |
Image Segmentation | PMD | SAM2-UNet | https://arxiv.org/abs/2408.08870v1 | IoU | 0.728 |
Image Segmentation | PMD | SAM2-UNet | https://arxiv.org/abs/2408.08870v1 | F-measure | 0.826 |
Image Segmentation | PMD | HetNet | https://arxiv.org/abs/2211.15644v1 | MAE | 0.029 |
Image Segmentation | PMD | HetNet | https://arxiv.org/abs/2211.15644v1 | IoU | 0.690 |
Image Segmentation | PMD | HetNet | https://arxiv.org/abs/2211.15644v1 | F-measure | 0.814 |
Image Segmentation | PMD | SANet | http://openaccess.thecvf.com//content/CVPR2022/html/Guan_Learning_Semantic_Associations_for_Mirror_Detection_CVPR_2022_paper.html | MAE | 0.032 |
Image Segmentation | PMD | SANet | http://openaccess.thecvf.com//content/CVPR2022/html/Guan_Learning_Semantic_Associations_for_Mirror_Detection_CVPR_2022_paper.html | IoU | 0.668 |
Image Segmentation | PMD | SANet | http://openaccess.thecvf.com//content/CVPR2022/html/Guan_Learning_Semantic_Associations_for_Mirror_Detection_CVPR_2022_paper.html | F-measure | 0.795 |
Image Segmentation | PMD | PMD | http://openaccess.thecvf.com/content_CVPR_2020/html/Lin_Progressive_Mirror_Detection_CVPR_2020_paper.html | MAE | 0.032 |
Image Segmentation | PMD | PMD | http://openaccess.thecvf.com/content_CVPR_2020/html/Lin_Progressive_Mirror_Detection_CVPR_2020_paper.html | IoU | 0.660 |
Image Segmentation | PMD | PMD | http://openaccess.thecvf.com/content_CVPR_2020/html/Lin_Progressive_Mirror_Detection_CVPR_2020_paper.html | F-measure | 0.794 |
Image Segmentation | PMD | MirrorNet | https://arxiv.org/abs/1908.09101v2 | MAE | 0.043 |
Image Segmentation | PMD | MirrorNet | https://arxiv.org/abs/1908.09101v2 | IoU | 0.585 |
Image Segmentation | PMD | MirrorNet | https://arxiv.org/abs/1908.09101v2 | F-measure | 0.741 |
Image Segmentation | ImageNet | MobileOne-S0 | https://arxiv.org/abs/2206.04040v2 | GFLOPs | 0.275 |
Image Segmentation | COCO val2017 | SynCo (ResNet-50) 200ep | https://arxiv.org/abs/2410.02401v5 | mask AP | 35.4 |
Image Segmentation | HuTu 80 | UNetR | https://www.sciencedirect.com/science/article/abs/pii/S1746809422006437 | Dice | 0.9843 |
Image Segmentation | HuTu 80 | PALED | https://www.sciencedirect.com/science/article/abs/pii/S1746809422006437 | Dice | 0.9775 |
Image Segmentation | EVD4UAV | yolov8x-seg | https://arxiv.org/abs/2403.05422v2 | Detection: Full (mAP@0.5) | 96.19 |
Image Segmentation | MARIDA | ResAttUNet | https://arxiv.org/abs/2210.08506v1 | IoU | 0.67 |
Image Segmentation | MARIDA | ResAttUNet | https://arxiv.org/abs/2210.08506v1 | F1@M | 0.95 |
Image Segmentation | MARIDA | UNet | https://doi.org/10.1371/journal.pone.0262247 | IoU | 0.57 |
Image Segmentation | MARIDA | UNet | https://doi.org/10.1371/journal.pone.0262247 | F1 | 0.69 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (M-RCNN+IMS 5-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 9.82 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (MTFA+IMS 5-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 9.61 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (M-RCNN+ITL 5-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 9.35 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (iFS-RCNN+IMS 5-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 9.03 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (M-RCNN+IMS 3-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 8.65 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (Res101-MTFA+ITL 1-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 8.48 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (M-RCNN+IMS 2-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 7.84 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (MTFA+IMS 3-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 7.36 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (MTFA+IMS 2-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 6.95 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (iFS-RCNN+IMS 2-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 6.83 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (iFS-RCNN+IMS 3-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 6.14 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (M-RCNN+ITL 2-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 6.01 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (MTFA+IMS 1-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 5.46 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (M-RCNN+ITL 1-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 5.35 |
Image Segmentation > Few-shot Instance Segmentation | CAMO-FS | FS-CDIS (iFS-RCNN+IMS 1-shot) | https://arxiv.org/abs/2304.07444v4 | mask AP | 2.99 |
MMLU | MMLU-Pro | Orange-mini | https://arxiv.org/abs/2501.13117v1 | 0-shot MRR | 99.19 |
One-Shot Segmentation | Cluttered Omniglot | MaskNet | http://arxiv.org/abs/1803.09597v2 | IoU [32 distractors] | 65.6 |
One-Shot Segmentation | Cluttered Omniglot | MaskNet | http://arxiv.org/abs/1803.09597v2 | IoU [4 distractors] | 95.8 |
One-Shot Segmentation | Cluttered Omniglot | MaskNet | http://arxiv.org/abs/1803.09597v2 | IoU [256 distractors] | 43.7 |
One-Shot Segmentation | Cluttered Omniglot | Siamese-U-Net | http://arxiv.org/abs/1803.09597v2 | IoU [32 distractors] | 62.4 |
One-Shot Segmentation | Cluttered Omniglot | Siamese-U-Net | http://arxiv.org/abs/1803.09597v2 | IoU [4 distractors] | 97.1 |
One-Shot Segmentation | Cluttered Omniglot | Siamese-U-Net | http://arxiv.org/abs/1803.09597v2 | IoU [256 distractors] | 38.4 |
Video deraining | VRDS | Turtle | https://arxiv.org/abs/2410.03936v2 | SSIM | 0.9590 |
Video deraining | VRDS | Turtle | https://arxiv.org/abs/2410.03936v2 | PSNR | 32.01 |
Video deraining | VRDS | RainMamba | https://arxiv.org/abs/2407.21773v2 | SSIM | 0.9366 |
Video deraining | VRDS | RainMamba | https://arxiv.org/abs/2407.21773v2 | PSNR | 32.04 |
Video deraining | VRDS | Restormer | https://arxiv.org/abs/2111.09881v2 | SSIM | 0.9206 |
Video deraining | VRDS | Restormer | https://arxiv.org/abs/2111.09881v2 | PSNR | 29.59 |
Video deraining | VRDS | MPRNet | https://arxiv.org/abs/2011.04566v1 | SSIM | 0.9175 |
Video deraining | VRDS | MPRNet | https://arxiv.org/abs/2011.04566v1 | PSNR | 29.53 |
Video deraining | VRDS | BasicVSR++ | https://arxiv.org/abs/2104.13371v1 | SSIM | 0.9171 |
Video deraining | VRDS | BasicVSR++ | https://arxiv.org/abs/2104.13371v1 | PSNR | 29.75 |
Video deraining | VRDS | TTVSR | https://arxiv.org/abs/2204.04216v3 | SSIM | 0.8998 |
Video deraining | VRDS | TTVSR | https://arxiv.org/abs/2204.04216v3 | PSNR | 28.05 |
Video deraining | VRDS | BasicVSR | https://arxiv.org/abs/2012.02181v2 | SSIM | 0.8990 |
Video deraining | VRDS | BasicVSR | https://arxiv.org/abs/2012.02181v2 | PSNR | 28.35 |
Video deraining | VRDS | RVRT | https://arxiv.org/abs/2206.02146v3 | SSIM | 0.8857 |
Video deraining | VRDS | RVRT | https://arxiv.org/abs/2206.02146v3 | PSNR | 28.24 |
Video deraining | Video Waterdrop Removal Dataset | RainMamba | https://arxiv.org/abs/2407.21773v2 | PSNR | 37.21 |
Video deraining | Video Waterdrop Removal Dataset | RainMamba | https://arxiv.org/abs/2407.21773v2 | SSIM | 0.9816 |
Video deraining | Video Waterdrop Removal Dataset | BasicVSR++ | https://arxiv.org/abs/2104.13371v1 | PSNR | 32.37 |
Video deraining | Video Waterdrop Removal Dataset | BasicVSR++ | https://arxiv.org/abs/2104.13371v1 | SSIM | 0.9792 |
Video deraining | Video Waterdrop Removal Dataset | VWR | https://arxiv.org/abs/2302.05916v3 | PSNR | 30.72 |
Video deraining | Video Waterdrop Removal Dataset | VWR | https://arxiv.org/abs/2302.05916v3 | SSIM | 0.9726 |
Video deraining | Video Waterdrop Removal Dataset | Vid2Vid | http://arxiv.org/abs/1808.06601v2 | PSNR | 28.73 |
Video deraining | Video Waterdrop Removal Dataset | Vid2Vid | http://arxiv.org/abs/1808.06601v2 | SSIM | 0.9542 |
Video deraining | Video Waterdrop Removal Dataset | CCN | http://openaccess.thecvf.com//content/CVPR2021/html/Quan_Removing_Raindrops_and_Rain_Streaks_in_One_Go_CVPR_2021_paper.html | PSNR | 27.53 |
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