Datasets:

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[ { "index": 2, "records": [ { "column": 2, "dataset": "SOP", "metric": "R@1", "model": "Cross-Batch Memory", "row": 16, "task": "Image Retrieval", "value": "80.6" } ] }, { "index": 3, "records": [ { "column": 2, "dataset": "In-Shop", "metric": "R@1", "model": "Cross-Batch Memory", "row": 11, "task": "Image Retrieval", "value": "91.3" } ] } ]

[ { "index": 5, "records": [ { "column": 1, "dataset": "Kinetics-Skeleton dataset", "metric": "Accuracy", "model": "MS-AAGCN", "row": 10, "task": "Skeleton Based Action Recognition", "value": "37.8" } ] }, { "index": 6, "records": [ { "column": 3, "dataset": "NTU RGB+D", "metric": "Accuracy (CS)", "model": "RNX3D101+MS-AAGCN-C", "row": 11, "task": "Skeleton Based Action Recognition", "value": "96.1" }, { "column": 4, "dataset": "NTU RGB+D", "metric": "Accuracy (CV)", "model": "RNX3D101+MS-AAGCN-C", "row": 11, "task": "Skeleton Based Action Recognition", "value": "99" } ] } ]

[ { "index": 6, "records": [ { "column": 2, "dataset": "Cityscapes val", "metric": "mIoU", "model": "SemanticFPN P2-P5 + PointRend", "row": 2, "task": "Semantic Segmentation", "value": "78.6" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "COCO", "metric": "Inception score", "model": "CPGAN", "row": 11, "task": "Text-to-Image Generation", "value": "52.73" } ] } ]

[ { "index": 2, "records": [ { "column": 1, "dataset": "BlogCatalog", "metric": "Micro F1", "model": "DAOR", "row": 15, "task": "Node Classification", "value": "33.05" }, { "column": 2, "dataset": "PPI", "metric": "Micro F1", "model": "DAOR", "row": 15, "task": "Node Classification", "value": "19.07" }, { "column": 3, "dataset": "Wiki", "metric": "Micro F1", "model": "DAOR", "row": 15, "task": "Node Classification", "value": "53.24" }, { "column": 4, "dataset": "DBLP", "metric": "Micro F1", "model": "DAOR", "row": 15, "task": "Node Classification", "value": "87.86" }, { "column": 5, "dataset": "BlogCatalog", "metric": "Macro F1", "model": "DAOR", "row": 15, "task": "Node Classification", "value": "17.25" }, { "column": 6, "dataset": "PPI", "metric": "Macro F1", "model": "DAOR", "row": 15, "task": "Node Classification", "value": "13.94" }, { "column": 7, "dataset": "Wiki", "metric": "Macro F1", "model": "DAOR", "row": 15, "task": "Node Classification", "value": "15.97" }, { "column": 8, "dataset": "DBLP", "metric": "Macro F1", "model": "DAOR", "row": 15, "task": "Node Classification", "value": "87.64" } ] } ]

[ { "index": 9, "records": [ { "column": 1, "dataset": "ICDAR 2015", "metric": "Recall", "model": "SBD", "row": 34, "task": "Scene Text Detection", "value": "88.2" }, { "column": 2, "dataset": "ICDAR 2015", "metric": "Precision", "model": "SBD", "row": 34, "task": "Scene Text Detection", "value": "92.1" }, { "column": 3, "dataset": "ICDAR 2015", "metric": "F-Measure", "model": "SBD", "row": 34, "task": "Scene Text Detection", "value": "90.1" } ] }, { "index": 10, "records": [ { "column": 1, "dataset": "ICDAR 2017 MLT", "metric": "Recall", "model": "SBD", "row": 12, "task": "Scene Text Detection", "value": "76.44" }, { "column": 2, "dataset": "ICDAR 2017 MLT", "metric": "Precision", "model": "SBD", "row": 12, "task": "Scene Text Detection", "value": "82.75" }, { "column": 3, "dataset": "ICDAR 2017 MLT", "metric": "F-Measure", "model": "SBD", "row": 12, "task": "Scene Text Detection", "value": "79.47" } ] } ]

[ { "index": 0, "records": [ { "column": 2, "dataset": "S3DIS", "metric": "mCov", "model": "JSNet", "row": 9, "task": "3D Instance Segmentation", "value": "54.1" }, { "column": 3, "dataset": "S3DIS", "metric": "mWCov", "model": "JSNet", "row": 9, "task": "3D Instance Segmentation", "value": "58" }, { "column": 4, "dataset": "S3DIS", "metric": "mRec", "model": "JSNet", "row": 9, "task": "3D Instance Segmentation", "value": "53.9" }, { "column": 5, "dataset": "S3DIS", "metric": "mPrec", "model": "JSNet", "row": 9, "task": "3D Instance Segmentation", "value": "66.9" } ] }, { "index": 1, "records": [ { "column": 2, "dataset": "S3DIS", "metric": "mAcc", "model": "JSNet", "row": 12, "task": "Semantic Segmentation", "value": "71.7" }, { "column": 3, "dataset": "S3DIS", "metric": "oAcc", "model": "JSNet", "row": 12, "task": "Semantic Segmentation", "value": "88.7" }, { "column": 4, "dataset": "S3DIS", "metric": "Mean IoU", "model": "JSNet", "row": 12, "task": "Semantic Segmentation", "value": "61.7" } ] }, { "index": 2, "records": [ { "column": 1, "dataset": "ShapeNet", "metric": "Mean IoU", "model": "JSNet", "row": 4, "task": "Semantic Segmentation", "value": "85.8" } ] } ]

[ { "index": 1, "records": [ { "column": 1, "dataset": "D&D", "metric": "Accuracy", "model": "DGCNN", "row": 2, "task": "Graph Classification", "value": "76.6" }, { "column": 2, "dataset": "NCI1", "metric": "Accuracy", "model": "DGCNN", "row": 2, "task": "Graph Classification", "value": "76.4" }, { "column": 3, "dataset": "PROTEINS", "metric": "Accuracy", "model": "DiffPool", "row": 3, "task": "Graph Classification", "value": "73.7" }, { "column": 2, "dataset": "NCI1", "metric": "Accuracy", "model": "GIN", "row": 5, "task": "Graph Classification", "value": "80" }, { "column": 4, "dataset": "ENZYMES", "metric": "Accuracy", "model": "GIN", "row": 5, "task": "Graph Classification", "value": "59.6" }, { "column": 3, "dataset": "PROTEINS", "metric": "Accuracy", "model": "GraphSAGE", "row": 6, "task": "Graph Classification", "value": "73" }, { "column": 4, "dataset": "ENZYMES", "metric": "Accuracy", "model": "GraphSAGE", "row": 6, "task": "Graph Classification", "value": "58.2" } ] }, { "index": 2, "records": [ { "column": 2, "dataset": "IMDb-B", "metric": "Accuracy", "model": "GraphSAGE", "row": 12, "task": "Graph Classification", "value": "68.8" }, { "column": 3, "dataset": "IMDb-M", "metric": "Accuracy", "model": "GraphSAGE", "row": 12, "task": "Graph Classification", "value": "47.6" }, { "column": 4, "dataset": "REDDIT-B", "metric": "Accuracy", "model": "GraphSAGE", "row": 12, "task": "Graph Classification", "value": "84.3" }, { "column": 5, "dataset": "REDDIT-MULTI-5k", "metric": "Accuracy", "model": "GraphSAGE", "row": 12, "task": "Graph Classification", "value": "50" }, { "column": 6, "dataset": "COLLAB", "metric": "Accuracy", "model": "GraphSAGE", "row": 12, "task": "Graph Classification", "value": "73.9" } ] } ]

[ { "index": 3, "records": [ { "column": 1, "dataset": "Cityscapes val", "metric": "mIoU", "model": "FasterSeg", "row": 8, "task": "Semantic Segmentation", "value": "73.1" }, { "column": 2, "dataset": "Cityscapes test", "metric": "Mean IoU (class)", "model": "FasterSeg", "row": 8, "task": "Semantic Segmentation", "value": "71.5" } ] }, { "index": 5, "records": [ { "column": 1, "dataset": "BDD", "metric": "mIoU", "model": "FasterSeg", "row": 3, "task": "Semantic Segmentation", "value": "55.1" } ] } ]

[ { "index": 1, "records": [ { "column": 8, "dataset": "LineMOD", "metric": "Mean ADD", "model": "W-PoseNet", "row": 15, "task": "6D Pose Estimation using RGBD", "value": "98.2" } ] } ]

[ { "index": 0, "records": [ { "column": 8, "dataset": "Dayton (256×256) - aerial-to-ground", "metric": "SSIM", "model": "LGGAN", "row": 10, "task": "Cross-View Image-to-Image Translation", "value": "0.5457" }, { "column": 9, "dataset": "Dayton (256×256) - aerial-to-ground", "metric": "PSNR", "model": "LGGAN", "row": 10, "task": "Cross-View Image-to-Image Translation", "value": "22.9949" }, { "column": 10, "dataset": "Dayton (256×256) - aerial-to-ground", "metric": "SD", "model": "LGGAN", "row": 10, "task": "Cross-View Image-to-Image Translation", "value": "19.6145" }, { "column": 11, "dataset": "Dayton (256×256) - aerial-to-ground", "metric": "KL", "model": "LGGAN", "row": 10, "task": "Cross-View Image-to-Image Translation", "value": "2.18" } ] }, { "index": 1, "records": [ { "column": 8, "dataset": "cvusa", "metric": "SSIM", "model": "LGGAN", "row": 11, "task": "Cross-View Image-to-Image Translation", "value": "0.5238" }, { "column": 9, "dataset": "cvusa", "metric": "PSNR", "model": "LGGAN", "row": 11, "task": "Cross-View Image-to-Image Translation", "value": "22.5766" }, { "column": 10, "dataset": "cvusa", "metric": "SD", "model": "LGGAN", "row": 11, "task": "Cross-View Image-to-Image Translation", "value": "19.744" }, { "column": 11, "dataset": "cvusa", "metric": "KL", "model": "LGGAN", "row": 11, "task": "Cross-View Image-to-Image Translation", "value": "2.55" } ] } ]

[ { "index": 0, "records": [ { "column": 3, "dataset": "KITTI Cars Easy", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "3D Object Detection", "value": "90.25" }, { "column": 4, "dataset": "KITTI Cars Moderate", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "3D Object Detection", "value": "81.43" }, { "column": 5, "dataset": "KITTI Cars Hard", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "3D Object Detection", "value": "76.82" }, { "column": 6, "dataset": "KITTI Cars Easy", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "Birds Eye View Object Detection", "value": "94.98" }, { "column": 7, "dataset": "KITTI Cars Moderate", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "Birds Eye View Object Detection", "value": "90.65" }, { "column": 8, "dataset": "KITTI Cars Hard", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "Birds Eye View Object Detection", "value": "86.14" }, { "column": 9, "dataset": "KITTI Cyclists Easy", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "3D Object Detection", "value": "78.60" }, { "column": 10, "dataset": "KITTI Cyclists Moderate", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "3D Object Detection", "value": "63.71" }, { "column": 11, "dataset": "KITTI Cyclists Hard", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "3D Object Detection", "value": "57.65" }, { "column": 12, "dataset": "KITTI Cyclists Easy", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "Birds Eye View Object Detection", "value": "82.49" }, { "column": 13, "dataset": "KITTI Cyclists Moderate", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "Birds Eye View Object Detection", "value": "68.89" }, { "column": 14, "dataset": "KITTI Cyclists Hard", "metric": "AP", "model": "PV-RCNN", "row": 15, "task": "Birds Eye View Object Detection", "value": "62.41" } ] } ]

[ { "index": 0, "records": [ { "column": 7, "dataset": "Office-31", "metric": "Average Accuracy", "model": "DADA", "row": 12, "task": "Domain Adaptation", "value": "88" } ] }, { "index": 1, "records": [ { "column": 7, "dataset": "ImageCLEF-DA", "metric": "Accuracy", "model": "DADA", "row": 8, "task": "Domain Adaptation", "value": "89.3" } ] } ]

[ { "index": 9, "records": [ { "column": 2, "dataset": "COCO panoptic", "metric": "PQ", "model": "Panoptic-FPN-VoVNet57", "row": 4, "task": "Panoptic Segmentation", "value": "44.3" } ] } ]

[ { "index": 4, "records": [ { "column": 1, "dataset": "Sbd val", "metric": "APvol", "model": "Deep snake", "row": 4, "task": "Semantic Contour Prediction", "value": "54.4" }, { "column": 2, "dataset": "Sbd val", "metric": "AP50", "model": "Deep snake", "row": 4, "task": "Semantic Contour Prediction", "value": "62.1" }, { "column": 3, "dataset": "Sbd val", "metric": "AP70", "model": "Deep snake", "row": 4, "task": "Semantic Contour Prediction", "value": "48.3" } ] } ]

[ { "index": 4, "records": [ { "column": 9, "dataset": "Derf’s Test Media 960×540", "metric": "PSNR", "model": "VBM3D ST+OF+MS", "row": 7, "task": "Grayscale Video Denoising", "value": "38.95" }, { "column": 9, "dataset": "Derf’s Test Media 960×540", "metric": "PSNR", "model": "VBM3D ST+OF+MS", "row": 14, "task": "Grayscale Video Denoising", "value": "35.67" }, { "column": 9, "dataset": "Derf’s Test Media 960×540", "metric": "PSNR", "model": "VBM3D ST+OF+MS", "row": 21, "task": "Grayscale Video Denoising", "value": "32.44" } ] } ]

[ { "index": 0, "records": [ { "column": 7, "dataset": "LineMOD", "metric": "Mean ADD", "model": "HybridPose", "row": 14, "task": "6D Pose Estimation using RGB", "value": "94.5" } ] }, { "index": 1, "records": [ { "column": 7, "dataset": "Occlusion LineMOD", "metric": "Mean ADD", "model": "HybridPose", "row": 9, "task": "6D Pose Estimation using RGB", "value": "79.2" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "Vid4 - 4x upscaling", "metric": "PSNR", "model": "SOF-VSR", "row": 8, "task": "Video Super-Resolution", "value": "26" }, { "column": 2, "dataset": "Vid4 - 4x upscaling", "metric": "SSIM", "model": "SOF-VSR", "row": 8, "task": "Video Super-Resolution", "value": "0.772" } ] } ]

[ { "index": 4, "records": [ { "column": 7, "dataset": "UCF101-24", "metric": "Video-mAP 0.2", "model": "MOC", "row": 13, "task": "Action Detection", "value": "81.8" }, { "column": 8, "dataset": "UCF101-24", "metric": "Video-mAP 0.5", "model": "Ours (MOC)", "row": 13, "task": "Action Detection", "value": "53.9" }, { "column": 9, "dataset": "UCF101-24", "metric": "Video-mAP 0.75", "model": "Ours (MOC)", "row": 13, "task": "Action Detection", "value": "28.5" }, { "column": 10, "dataset": "UCF101-24", "metric": "mAP", "model": "Ours (MOC)", "row": 13, "task": "Action Detection", "value": "27.7" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "Con-Text", "metric": "mAP", "model": "PHOC descriptor + Fisher Vector Encoding", "row": 5, "task": "Fine-Grained Image Classification", "value": "80.2" }, { "column": 2, "dataset": "Bottles", "metric": "mAP", "model": "PHOC descriptor + Fisher Vector Encoding", "row": 5, "task": "Fine-Grained Image Classification", "value": "77.4" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "ImageNet", "metric": "Top 1 Accuracy", "model": "Assemble-ResNet152", "row": 6, "task": "Image Classification", "value": "84.2" } ] }, { "index": 7, "records": [ { "column": 4, "dataset": "Food-101", "metric": "Top 1 Accuracy", "model": "Assemble-ResNet-FGVC-50", "row": 14, "task": "Fine-Grained Image Classification", "value": "92.47" } ] }, { "index": 8, "records": [ { "column": 4, "dataset": "Stanford Cars", "metric": "Accuracy", "model": "Assemble-ResNet-FGVC-50", "row": 2, "task": "Fine-Grained Image Classification", "value": "94.4" }, { "column": 4, "dataset": "Oxford 102 Flowers", "metric": "Accuracy", "model": "Assemble-ResNet-FGVC-50", "row": 3, "task": "Fine-Grained Image Classification", "value": "98.9" }, { "column": 4, "dataset": "FGVC Aircraft", "metric": "Accuracy", "model": "Assemble-ResNet-FGVC-50", "row": 4, "task": "Fine-Grained Image Classification", "value": "92.4" }, { "column": 4, "dataset": "Oxford-IIIT Pets", "metric": "Accuracy", "model": "Assemble-ResNet-FGVC-50", "row": 5, "task": "Fine-Grained Image Classification", "value": "94.3" } ] }, { "index": 9, "records": [ { "column": 3, "dataset": "SOP", "metric": "Recall@1", "model": "Assemble-ResNet-FGVC-50", "row": 9, "task": "Fine-Grained Image Classification", "value": "85.9" } ] } ]

[ { "index": 2, "records": [ { "column": 15, "dataset": "DAVIS 2016", "metric": "Jaccard (Mean)", "model": "COSNet", "row": 2, "task": "Video Object Segmentation", "value": "80.5" }, { "column": 15, "dataset": "DAVIS 2016", "metric": "Jaccard (Recall)", "model": "COSNet", "row": 3, "task": "Video Object Segmentation", "value": "94" }, { "column": 15, "dataset": "DAVIS 2016", "metric": "Jaccard (Decay)", "model": "COSNet", "row": 4, "task": "Video Object Segmentation", "value": "0" }, { "column": 15, "dataset": "DAVIS 2016", "metric": "F-measure (Mean)", "model": "COSNet", "row": 5, "task": "Video Object Segmentation", "value": "79.4" }, { "column": 15, "dataset": "DAVIS 2016", "metric": "F-measure (Recall)", "model": "COSNet", "row": 6, "task": "Video Object Segmentation", "value": "90.4" }, { "column": 15, "dataset": "DAVIS 2016", "metric": "F-measure (Mean)", "model": "COSNet", "row": 7, "task": "Video Object Segmentation", "value": "0" } ] }, { "index": 3, "records": [ { "column": 5, "dataset": "FBMS", "metric": "Jaccard (Mean)", "model": "COSNet", "row": 3, "task": "Video Object Segmentation", "value": "75.6" } ] }, { "index": 4, "records": [ { "column": 8, "dataset": "YouTube", "metric": "mIoU", "model": "COSNet", "row": 12, "task": "Video Object Segmentation", "value": "70.5" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "NPE", "metric": "User Study Score", "model": "Zero-DCE", "row": 7, "task": "Low-Light Image Enhancement", "value": "3.81" }, { "column": 2, "dataset": "LIME", "metric": "User Study Score", "model": "Zero-DCE", "row": 7, "task": "Low-Light Image Enhancement", "value": "3.8" }, { "column": 3, "dataset": "MEF", "metric": "User Study Score", "model": "Zero-DCE", "row": 7, "task": "Low-Light Image Enhancement", "value": "4.13" }, { "column": 4, "dataset": "DICM", "metric": "User Study Score", "model": "Zero-DCE", "row": 7, "task": "Low-Light Image Enhancement", "value": "3.52" }, { "column": 5, "dataset": "VV", "metric": "User Study Score", "model": "Zero-DCE", "row": 7, "task": "Low-Light Image Enhancement", "value": "3.24" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "Market-1501", "metric": "MAP", "model": "PLR-OSNet", "row": 21, "task": "Person Re-Identification", "value": "88.9" }, { "column": 2, "dataset": "Market-1501", "metric": "Rank-1", "model": "PLR-OSNet", "row": 21, "task": "Person Re-Identification", "value": "95.6" } ] }, { "index": 1, "records": [ { "column": 1, "dataset": "DukeMTMC-reID", "metric": "MAP", "model": "PLR-OSNet", "row": 18, "task": "Person Re-Identification", "value": "81.2" }, { "column": 2, "dataset": "DukeMTMC-reID", "metric": "Rank-1", "model": "PLR-OSNet", "row": 18, "task": "Person Re-Identification", "value": "91.6" } ] }, { "index": 2, "records": [ { "column": 1, "dataset": "CUHK03 labeled", "metric": "MAP", "model": "PLR-OSNet", "row": 14, "task": "Person Re-Identification", "value": "80.5" }, { "column": 2, "dataset": "CUHK03 labeled", "metric": "Rank-1", "model": "PLR-OSNet", "row": 14, "task": "Person Re-Identification", "value": "84.6" }, { "column": 3, "dataset": "CUHK03 detected", "metric": "MAP", "model": "PLR-OSNet", "row": 14, "task": "Person Re-Identification", "value": "77.2" }, { "column": 4, "dataset": "CUHK03 detected", "metric": "Rank-1", "model": "PLR-OSNet", "row": 14, "task": "Person Re-Identification", "value": "80.4" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "SUN09", "metric": "Endocardium Dice", "model": "SAUNet", "row": 6, "task": "Left Ventricle Segmentation", "value": "0.952" }, { "column": 2, "dataset": "SUN09", "metric": "Epicardium Dice", "model": "SAUNet", "row": 6, "task": "Left Ventricle Segmentation", "value": "0.962" } ] }, { "index": 1, "records": [ { "column": 1, "dataset": "AC17", "metric": "Dice Score", "model": "SAUNet", "row": 6, "task": "Left Ventricle Segmentation", "value": "0.938" }, { "column": 2, "dataset": "AC17", "metric": "Dice Score", "model": "SAUNet", "row": 6, "task": "Right Ventricle Segmentation", "value": "0.914" }, { "column": 3, "dataset": "AC17", "metric": "Dice Score", "model": "SAUNet", "row": 6, "task": "Myocardium Segmentation", "value": "0.887" } ] } ]

[ { "index": 1, "records": [ { "column": 4, "dataset": "CIFAR-100, 400 Labels", "metric": "Percentage error", "model": "FixMatch (CTA)", "row": 9, "task": "Semi-Supervised Image Classification", "value": "49.95" }, { "column": 7, "dataset": "SVHN, 40 Labels", "metric": "Percentage error", "model": "FixMatch (CTA)", "row": 9, "task": "Semi-Supervised Image Classification", "value": "7.65" }, { "column": 9, "dataset": "SVHN, 1000 labels", "metric": "Accuracy", "model": "FixMatch (CTA)", "row": 9, "task": "Semi-Supervised Image Classification", "value": "97.64" } ] } ]

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