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 ⌀ |
|---|---|---|---|---|---|
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PNS+ | https://arxiv.org/abs/2203.14291v3 | mean F-measure | 0.709 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PNS+ | https://arxiv.org/abs/2203.14291v3 | Dice | 0.737 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PNS+ | https://arxiv.org/abs/2203.14291v3 | Sensitivity | 0.623 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | MAT | https://www.researchgate.net/publication/343623463_MATNet_Motion-Attentive_Transition_Network_for_Zero-Shot_Video_Object_Segmentation | S-Measure | 0.785 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | MAT | https://www.researchgate.net/publication/343623463_MATNet_Motion-Attentive_Transition_Network_for_Zero-Shot_Video_Object_Segmentation | mean E-measure | 0.755 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | MAT | https://www.researchgate.net/publication/343623463_MATNet_Motion-Attentive_Transition_Network_for_Zero-Shot_Video_Object_Segmentation | weighted F-measure | 0.578 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | MAT | https://www.researchgate.net/publication/343623463_MATNet_Motion-Attentive_Transition_Network_for_Zero-Shot_Video_Object_Segmentation | mean F-measure | 0.645 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | MAT | https://www.researchgate.net/publication/343623463_MATNet_Motion-Attentive_Transition_Network_for_Zero-Shot_Video_Object_Segmentation | Dice | 0.712 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | MAT | https://www.researchgate.net/publication/343623463_MATNet_Motion-Attentive_Transition_Network_for_Zero-Shot_Video_Object_Segmentation | Sensitivity | 0.579 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | ACSNet | null | S-Measure | 0.783 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | ACSNet | null | mean E-measure | 0.787 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | ACSNet | null | weighted F-measure | 0.636 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | ACSNet | null | mean F-measure | 0.684 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | ACSNet | null | Dice | 0.708 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | ACSNet | null | Sensitivity | 0.618 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | 2/3D | null | S-Measure | 0.786 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | 2/3D | null | mean E-measure | 0.775 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | 2/3D | null | weighted F-measure | 0.634 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | 2/3D | null | mean F-measure | 0.688 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | 2/3D | null | Dice | 0.706 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | 2/3D | null | Sensitivity | 0.607 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | FSNet | https://arxiv.org/abs/2108.03151v3 | S-Measure | 0.724 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | FSNet | https://arxiv.org/abs/2108.03151v3 | mean E-measure | 0.694 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | FSNet | https://arxiv.org/abs/2108.03151v3 | weighted F-measure | 0.541 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | FSNet | https://arxiv.org/abs/2108.03151v3 | mean F-measure | 0.611 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | FSNet | https://arxiv.org/abs/2108.03151v3 | Dice | 0.699 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | FSNet | https://arxiv.org/abs/2108.03151v3 | Sensitivity | 0.491 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PNSNet | https://arxiv.org/abs/2105.08468v2 | S-Measure | 0.767 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PNSNet | https://arxiv.org/abs/2105.08468v2 | mean E-measure | 0.755 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PNSNet | https://arxiv.org/abs/2105.08468v2 | weighted F-measure | 0.609 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PNSNet | https://arxiv.org/abs/2105.08468v2 | mean F-measure | 0.656 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PNSNet | https://arxiv.org/abs/2105.08468v2 | Dice | 0.675 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PNSNet | https://arxiv.org/abs/2105.08468v2 | Sensitivity | 0.579 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | COSNet | https://arxiv.org/abs/2001.06810v1 | S-Measure | 0.670 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | COSNet | https://arxiv.org/abs/2001.06810v1 | mean E-measure | 0.627 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | COSNet | https://arxiv.org/abs/2001.06810v1 | weighted F-measure | 0.443 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | COSNet | https://arxiv.org/abs/2001.06810v1 | mean F-measure | 0.506 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | COSNet | https://arxiv.org/abs/2001.06810v1 | Dice | 0.606 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | COSNet | https://arxiv.org/abs/2001.06810v1 | Sensitivity | 0.380 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PraNet | https://arxiv.org/abs/2006.11392v4 | S-Measure | 0.717 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PraNet | https://arxiv.org/abs/2006.11392v4 | mean E-measure | 0.735 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PraNet | https://arxiv.org/abs/2006.11392v4 | weighted F-measure | 0.544 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PraNet | https://arxiv.org/abs/2006.11392v4 | mean F-measure | 0.607 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PraNet | https://arxiv.org/abs/2006.11392v4 | Dice | 0.598 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PraNet | https://arxiv.org/abs/2006.11392v4 | Sensitivity | 0.512 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | SANet | https://arxiv.org/abs/2108.00882v1 | S-Measure | 0.706 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | SANet | https://arxiv.org/abs/2108.00882v1 | mean E-measure | 0.743 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | SANet | https://arxiv.org/abs/2108.00882v1 | weighted F-measure | 0.526 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | SANet | https://arxiv.org/abs/2108.00882v1 | mean F-measure | 0.580 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | SANet | https://arxiv.org/abs/2108.00882v1 | Dice | 0.598 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | SANet | https://arxiv.org/abs/2108.00882v1 | Sensitivity | 0.505 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PCSA | null | S-Measure | 0.682 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PCSA | null | mean E-measure | 0.660 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PCSA | null | weighted F-measure | 0.443 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PCSA | null | mean F-measure | 0.510 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PCSA | null | Dice | 0.584 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | PCSA | null | Sensitivity | 0.415 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | DCF | http://openaccess.thecvf.com//content/ICCV2021/html/Zhang_Dynamic_Context-Sensitive_Filtering_Network_for_Video_Salient_Object_Detection_ICCV_2021_paper.html | S-Measure | 0.514 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | DCF | http://openaccess.thecvf.com//content/ICCV2021/html/Zhang_Dynamic_Context-Sensitive_Filtering_Network_for_Video_Salient_Object_Detection_ICCV_2021_paper.html | mean E-measure | 0.522 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | DCF | http://openaccess.thecvf.com//content/ICCV2021/html/Zhang_Dynamic_Context-Sensitive_Filtering_Network_for_Video_Salient_Object_Detection_ICCV_2021_paper.html | weighted F-measure | 0.263 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | DCF | http://openaccess.thecvf.com//content/ICCV2021/html/Zhang_Dynamic_Context-Sensitive_Filtering_Network_for_Video_Salient_Object_Detection_ICCV_2021_paper.html | mean F-measure | 0.303 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | DCF | http://openaccess.thecvf.com//content/ICCV2021/html/Zhang_Dynamic_Context-Sensitive_Filtering_Network_for_Video_Salient_Object_Detection_ICCV_2021_paper.html | Dice | 0.317 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | DCF | http://openaccess.thecvf.com//content/ICCV2021/html/Zhang_Dynamic_Context-Sensitive_Filtering_Network_for_Video_Salient_Object_Detection_ICCV_2021_paper.html | Sensitivity | 0.364 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | AMD | https://arxiv.org/abs/2111.06394v1 | S-Measure | 0.472 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | AMD | https://arxiv.org/abs/2111.06394v1 | mean E-measure | 0.527 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | AMD | https://arxiv.org/abs/2111.06394v1 | weighted F-measure | 0.128 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | AMD | https://arxiv.org/abs/2111.06394v1 | mean F-measure | 0.141 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | AMD | https://arxiv.org/abs/2111.06394v1 | Dice | 0.252 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | AMD | https://arxiv.org/abs/2111.06394v1 | Sensitivity | 0.213 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | UNet++ | http://arxiv.org/abs/1807.10165v1 | Sensitivity | 0.467 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Hard (Unseen) | UNet | http://arxiv.org/abs/1505.04597v1 | Sensitivity | 0.429 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | LGRNet | https://arxiv.org/abs/2407.05703v1 | Dice | 0.875 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | LGRNet | https://arxiv.org/abs/2407.05703v1 | IoU | 0.810 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | MS-TFAL | https://arxiv.org/abs/2307.05898v1 | Dice | 0.859 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | MS-TFAL | https://arxiv.org/abs/2307.05898v1 | IoU | 0.792 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | FLA-Net | https://arxiv.org/abs/2310.01861v1 | Dice | 0.856 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | FLA-Net | https://arxiv.org/abs/2310.01861v1 | IoU | 0.784 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | WeakPolyP | https://arxiv.org/abs/2307.10912v1 | Dice | 0.853 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | WeakPolyP | https://arxiv.org/abs/2307.10912v1 | IoU | 0.781 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | UNet++ | http://arxiv.org/abs/1807.10165v1 | S measure | 0.684 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | UNet++ | http://arxiv.org/abs/1807.10165v1 | mean E-measure | 0.687 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | UNet++ | http://arxiv.org/abs/1807.10165v1 | weighted F-measure | 0.491 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | UNet++ | http://arxiv.org/abs/1807.10165v1 | mean F-measure | 0.553 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | UNet++ | http://arxiv.org/abs/1807.10165v1 | Dice | 0.559 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | UNet | http://arxiv.org/abs/1505.04597v1 | S measure | 0.669 |
Medical Image Segmentation > Video Polyp Segmentation | SUN-SEG-Easy | UNet | http://arxiv.org/abs/1505.04597v1 | mean E-measure | 0.677 |
Medical Image Segmentation > Video Polyp Segmentation | STARE | UNet | http://arxiv.org/abs/1505.04597v1 | AUC | 0.459 |
Medical Image Segmentation > Brain Image Segmentation | Brain Tumor | UNet++ | https://arxiv.org/abs/1912.05074v2 | IoU | 91.21 |
Medical Image Segmentation > Brain Image Segmentation | FIB-25 Whole Test | U-NET MALA | https://arxiv.org/abs/1709.02974v4 | VOI | 1.071 |
Medical Image Segmentation > Brain Image Segmentation | FIB-25 Synaptic Sites | U-NET MALA | https://arxiv.org/abs/1709.02974v4 | VOI | 2.151 |
Medical Image Segmentation > Brain Image Segmentation | CREMI | U-NET MALA | https://arxiv.org/abs/1709.02974v4 | VOI | 0.606 |
Medical Image Segmentation > Brain Image Segmentation | CREMI | U-NET MALA | https://arxiv.org/abs/1709.02974v4 | CREMI Score | 0.289 |
Medical Image Segmentation > Brain Image Segmentation | SegEM | U-NET MALA | https://arxiv.org/abs/1709.02974v4 | IED | 4.839 |
Medical Image Segmentation > Brain Image Segmentation | T1-weighted MRI | Learned Transformations (random augmentaiton) | http://arxiv.org/abs/1902.09383v2 | Dice Score | 81.5 |
Medical Image Segmentation > Lung Nodule Segmentation | Lung Nodule | BCDU-net | https://arxiv.org/abs/1909.00166v1 | Dice Score | 0.994 |
Medical Image Segmentation > Lung Nodule Segmentation | LIDC-IDRI | ModelGenesis | https://arxiv.org/abs/1908.06912v1 | IoU | 77.62 |
Medical Image Segmentation > Lung Nodule Segmentation | LIDC-IDRI | ModelGenesis | https://arxiv.org/abs/1908.06912v1 | Dice | 75.86 |
Medical Image Segmentation > Lung Nodule Segmentation | LIDC-IDRI | Semantic Genesis | https://arxiv.org/abs/2007.06959v1 | IoU | 77.24 |
Medical Image Segmentation > Lung Nodule Segmentation | Montgomery County | ET-Net | https://arxiv.org/abs/1907.10936v1 | Accuracy | 0.9865 |
Medical Image Segmentation > Lung Nodule Segmentation | Montgomery County | ET-Net | https://arxiv.org/abs/1907.10936v1 | mIoU | 0.942 |
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