Datasets:

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[ { "index": 0, "records": [ { "column": 1, "dataset": "MuPoTS-3D", "metric": "MPJPE", "model": "Depth Prediction Network", "row": 4, "task": "3D Multi-person Pose Estimation (absolute)", "value": "292" }, { "column": 2, "dataset": "MuPoTS-3D", "metric": "MPJPE", "model": "Depth Prediction Network", "row": 4, "task": "3D Multi-person Pose Estimation (root-relative)", "value": "120" } ] } ]

[ { "index": 1, "records": [ { "column": 1, "dataset": "SUN - 0-Shot", "metric": "Accuracy", "model": "TAFE-Net", "row": 14, "task": "Few-Shot Image Classification", "value": "60.9" }, { "column": 2, "dataset": "CUB-200 - 0-Shot Learning", "metric": "Accuracy", "model": "TAFE-Net", "row": 14, "task": "Few-Shot Image Classification", "value": "56.9" }, { "column": 3, "dataset": "AWA1 - 0-Shot", "metric": "Accuracy", "model": "TAFE-Net", "row": 14, "task": "Few-Shot Image Classification", "value": "70.8" }, { "column": 4, "dataset": "AWA2 - 0-Shot", "metric": "Accuracy", "model": "TAFE-Net", "row": 14, "task": "Few-Shot Image Classification", "value": "69.3" }, { "column": 5, "dataset": "aPY - 0-Shot", "metric": "Accuracy", "model": "TAFE-Net", "row": 14, "task": "Few-Shot Image Classification", "value": "42.2" } ] } ]

[ { "index": 2, "records": [ { "column": 1, "dataset": "CUB-200-2011", "metric": "R@1", "model": "MS512", "row": 11, "task": "Image Retrieval", "value": "65.7" }, { "column": 7, "dataset": "CARS196", "metric": "R@1", "model": "MS512", "row": 11, "task": "Image Retrieval", "value": "84.1" } ] }, { "index": 3, "records": [ { "column": 1, "dataset": "In-Shop", "metric": "R@1", "model": "MS512", "row": 7, "task": "Image Retrieval", "value": "89.7" } ] }, { "index": 4, "records": [ { "column": 1, "dataset": "SOP", "metric": "R@1", "model": "MS512", "row": 10, "task": "Image Retrieval", "value": "78.2" } ] } ]

[ { "index": 1, "records": [ { "column": 1, "dataset": "CIFAR-10", "metric": "NMI", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.496" }, { "column": 2, "dataset": "CIFAR-10", "metric": "Accuracy", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.623" }, { "column": 4, "dataset": "CIFAR-100", "metric": "NMI", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.285" }, { "column": 5, "dataset": "CIFAR-100", "metric": "Accuracy", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.327" }, { "column": 7, "dataset": "STL-10", "metric": "NMI", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.376" }, { "column": 8, "dataset": "STL-10", "metric": "Accuracy", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.48200000000000004" }, { "column": 10, "dataset": "ImageNet-10", "metric": "NMI", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.608" }, { "column": 11, "dataset": "ImageNet-10", "metric": "Accuracy", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.71" }, { "column": 13, "dataset": "Imagenet-dog-15", "metric": "NMI", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.321" }, { "column": 14, "dataset": "Imagenet-dog-15", "metric": "Accuracy", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.38299999999999995" }, { "column": 16, "dataset": "Tiny-ImageNet", "metric": "NMI", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.22399999999999998" }, { "column": 17, "dataset": "Tiny-ImageNet", "metric": "Accuracy", "model": "DCCM", "row": 14, "task": "Image Clustering", "value": "0.10800000000000001" } ] } ]

[ { "index": 2, "records": [ { "column": 5, "dataset": "MSMT17", "metric": "Rank-1", "model": "DG-Net", "row": 5, "task": "Person Re-Identification", "value": "77.2" }, { "column": 6, "dataset": "MSMT17", "metric": "mAP", "model": "DG-Net", "row": 5, "task": "Person Re-Identification", "value": "52.3" } ] }, { "index": 8, "records": [ { "column": 2, "dataset": "CUHK03", "metric": "MAP", "model": "DG-Net", "row": 6, "task": "Person Re-Identification", "value": "61.1" } ] } ]

[ { "index": 0, "records": [ { "column": 5, "dataset": "COCO", "metric": "MAP", "model": "NAS-FPN AmoebaNet (7 @ 384) + DropBlock", "row": 24, "task": "Real-Time Object Detection", "value": "48.3" } ] } ]

[ { "index": 1, "records": [ { "column": 10, "dataset": "BSD68 sigma15", "metric": "PSNR", "model": "RIDNet", "row": 2, "task": "Grayscale Image Denoising", "value": "31.81" }, { "column": 10, "dataset": "BSD68 sigma25", "metric": "PSNR", "model": "RIDNet", "row": 3, "task": "Grayscale Image Denoising", "value": "29.34" }, { "column": 10, "dataset": "BSD68 sigma50", "metric": "PSNR", "model": "RIDNet", "row": 4, "task": "Grayscale Image Denoising", "value": "26.4" } ] }, { "index": 3, "records": [ { "column": 8, "dataset": "BSD68 sigma15", "metric": "PSNR", "model": "RIDNet", "row": 2, "task": "Color Image Denoising", "value": "34.01" }, { "column": 8, "dataset": "BSD68 sigma25", "metric": "PSNR", "model": "RIDNet", "row": 3, "task": "Color Image Denoising", "value": "31.37" }, { "column": 8, "dataset": "BSD68 sigma50", "metric": "PSNR", "model": "RIDNet", "row": 4, "task": "Color Image Denoising", "value": "28.14" } ] }, { "index": 4, "records": [ { "column": 2, "dataset": "Darmstadt Noise Dataset", "metric": "PSNR (sRGB)", "model": "RIDNet (blind)", "row": 18, "task": "Color Image Denoising", "value": "39.23" }, { "column": 3, "dataset": "Darmstadt Noise Dataset", "metric": "SSIM (sRGB)", "model": "RIDNet (blind)", "row": 18, "task": "Color Image Denoising", "value": "0.9526" } ] } ]

[ { "index": 1, "records": [ { "column": 2, "dataset": "THUMOS’14", "metric": "mAP [email protected]", "model": "Decouple-SSAD", "row": 16, "task": "Temporal Action Localization", "value": "60.2" }, { "column": 3, "dataset": "THUMOS’14", "metric": "mAP [email protected]", "model": "Decouple-SSAD", "row": 16, "task": "Temporal Action Localization", "value": "54.1" }, { "column": 4, "dataset": "THUMOS’14", "metric": "mAP [email protected]", "model": "Decouple-SSAD", "row": 16, "task": "Temporal Action Localization", "value": "44.2" }, { "column": 5, "dataset": "THUMOS’14", "metric": "mAP [email protected]", "model": "Decouple-SSAD", "row": 16, "task": "Temporal Action Localization", "value": "32.3" }, { "column": 6, "dataset": "THUMOS’14", "metric": "mAP [email protected]", "model": "Decouple-SSAD", "row": 16, "task": "Temporal Action Localization", "value": "19.1" } ] } ]

[ { "index": 0, "records": [ { "column": 5, "dataset": "MUSIC (multi-source)", "metric": "SIR", "model": "Co-Separation", "row": 5, "task": "Audio Source Separation", "value": "13.8" }, { "column": 6, "dataset": "MUSIC (multi-source)", "metric": "SAR", "model": "Co-Separation", "row": 5, "task": "Audio Source Separation", "value": "11.3" } ] }, { "index": 1, "records": [ { "column": 1, "dataset": "AudioSet", "metric": "SDR", "model": "Co-Separation", "row": 5, "task": "Audio Source Separation", "value": "4.26" }, { "column": 2, "dataset": "AudioSet", "metric": "SIR", "model": "Co-Separation", "row": 5, "task": "Audio Source Separation", "value": "7.07" }, { "column": 3, "dataset": "AudioSet", "metric": "SAR", "model": "Co-Separation", "row": 5, "task": "Audio Source Separation", "value": "13" } ] }, { "index": 3, "records": [ { "column": 1, "dataset": "AV-Bench - Wooden Horse", "metric": "NSDR", "model": "Co-Separation", "row": 5, "task": "Audio Denoising", "value": "14.5" }, { "column": 2, "dataset": "AV-Bench - Violin Yanni", "metric": "NSDR", "model": "Co-Separation", "row": 5, "task": "Audio Denoising", "value": "8.53" }, { "column": 3, "dataset": "AV-Bench - Guitar Solo", "metric": "NSDR", "model": "Co-Separation", "row": 5, "task": "Audio Denoising", "value": "11.9" } ] } ]

[ { "index": 2, "records": [ { "column": 4, "dataset": "NCI109", "metric": "Accuracy", "model": "SAGPool_g", "row": 3, "task": "Graph Classification", "value": "74.06" }, { "column": 1, "dataset": "D&D", "metric": "Accuracy", "model": "SAGPool_h", "row": 6, "task": "Graph Classification", "value": "76.45" }, { "column": 2, "dataset": "PROTEINS", "metric": "Accuracy", "model": "SAGPool_h", "row": 6, "task": "Graph Classification", "value": "71.86" } ] } ]

[ { "index": 0, "records": [ { "column": 2, "dataset": "Set5 - 4x upscaling", "metric": "PSNR", "model": "AdaFM-Net", "row": 1, "task": "Image Super-Resolution", "value": "32.13" }, { "column": 2, "dataset": "CBSD68 sigma15", "metric": "PSNR", "model": "AdaFM-Net", "row": 3, "task": "Color Image Denoising", "value": "34.1" } ] }, { "index": 2, "records": [ { "column": 3, "dataset": "Set5 - 3x upscaling", "metric": "PSNR", "model": "AdaFM-Net", "row": 1, "task": "Image Super-Resolution", "value": "34.34" }, { "column": 3, "dataset": "CBSD68 sigma75", "metric": "PSNR", "model": "AdaFM-Net", "row": 6, "task": "Color Image Denoising", "value": "26.35" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "TREC-PM", "metric": "mAP", "model": "BERT + Doc2query", "row": 11, "task": "Passage Re-Ranking", "value": "36.5" }, { "column": 2, "dataset": "MS MARCO", "metric": "MRR", "model": "BERT + Doc2query", "row": 11, "task": "Passage Re-Ranking", "value": "0.368" } ] } ]

[ { "index": 1, "records": [ { "column": 3, "dataset": "Reuters-21578", "metric": "F1", "model": "KD-LSTMreg", "row": 13, "task": "Document Classification", "value": "88.9" }, { "column": 5, "dataset": "AAPD", "metric": "F1", "model": "KD-LSTMreg", "row": 13, "task": "Document Classification", "value": "72.9" }, { "column": 7, "dataset": "IMDb", "metric": "Accuracy", "model": "KD-LSTMreg", "row": 13, "task": "Text Classification", "value": "53.7" }, { "column": 9, "dataset": "Yelp-14", "metric": "Accuracy", "model": "KD-LSTMreg", "row": 13, "task": "Document Classification", "value": "69.4" } ] } ]

[ { "index": 0, "records": [ { "column": 4, "dataset": "ECSSD", "metric": "F-measure", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "91.7" }, { "column": 5, "dataset": "ECSSD", "metric": "MAE", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "0.037" }, { "column": 7, "dataset": "HKU-IS", "metric": "F-measure", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "89.1" }, { "column": 8, "dataset": "HKU-IS", "metric": "MAE", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "0.034" }, { "column": 10, "dataset": "DUT-OMRON", "metric": "F-measure", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "74.7" }, { "column": 11, "dataset": "DUT-OMRON", "metric": "MAE", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "0.056" }, { "column": 13, "dataset": "DUTS-test", "metric": "F-measure", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "80.5" }, { "column": 14, "dataset": "DUTS-test", "metric": "MAE", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "0.043" }, { "column": 16, "dataset": "PASCAL-S", "metric": "F-measure", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "82.4" }, { "column": 17, "dataset": "PASCAL-S", "metric": "MAE", "model": "CPD-R (ResNet50)", "row": 14, "task": "Salient Object Detection", "value": "0.072" } ] }, { "index": 4, "records": [ { "column": 1, "dataset": "SBU", "metric": "Balanced Error Rate", "model": "CPD", "row": 10, "task": "Salient Object Detection", "value": "4.19" }, { "column": 2, "dataset": "ISTD", "metric": "Balanced Error Rate", "model": "CPD", "row": 10, "task": "Salient Object Detection", "value": "6.76" }, { "column": 3, "dataset": "UCF", "metric": "Balanced Error Rate", "model": "CPD", "row": 10, "task": "Salient Object Detection", "value": "7.21" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "MUTAG", "metric": "Accuracy", "model": "edGNN (avg)", "row": 4, "task": "Graph Classification", "value": "86.9" }, { "column": 1, "dataset": "MUTAG", "metric": "Accuracy", "model": "edGNN (max)", "row": 5, "task": "Graph Classification", "value": "88.8" } ] } ]

[ { "index": 1, "records": [ { "column": 3, "dataset": "LibriSpeech test-clean", "metric": "Word Error Rate (WER)", "model": "LAS (no LM)", "row": 13, "task": "Speech Recognition", "value": "3.2" }, { "column": 4, "dataset": "LibriSpeech test-other", "metric": "Word Error Rate (WER)", "model": "LAS (no LM)", "row": 13, "task": "Speech Recognition", "value": "7.7" }, { "column": 5, "dataset": "LibriSpeech test-clean", "metric": "Word Error Rate (WER)", "model": "LAS (no LM)", "row": 13, "task": "Speech Recognition", "value": "2.7" }, { "column": 6, "dataset": "LibriSpeech test-other", "metric": "Word Error Rate (WER)", "model": "LAS (no LM)", "row": 13, "task": "Speech Recognition", "value": "6.5" } ] }, { "index": 2, "records": [ { "column": 3, "dataset": "LibriSpeech test-clean", "metric": "Word Error Rate (WER)", "model": "LAS + SpecAugment ", "row": 20, "task": "Speech Recognition", "value": "2.5" }, { "column": 4, "dataset": "LibriSpeech test-other", "metric": "Word Error Rate (WER)", "model": "LAS + SpecAugment", "row": 20, "task": "Speech Recognition", "value": "5.8" } ] }, { "index": 4, "records": [ { "column": 3, "dataset": "Hub5'00 SwitchBoard", "metric": "SwitchBoard", "model": "LAS + SpecAugment (with LM, Switchboard mild policy)", "row": 19, "task": "Speech Recognition", "value": "6.8" }, { "column": 4, "dataset": "Hub5'00 SwitchBoard", "metric": "CallHome", "model": "LAS + SpecAugment (with LM, Switchboard strong policy)", "row": 20, "task": "Speech Recognition", "value": "14" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "VQA v2 test-dev", "metric": "Accuracy", "model": "Pythia v0.3 + LoRRA", "row": 7, "task": "Visual Question Answering", "value": "69.21" }, { "column": 1, "dataset": "VizWiz", "metric": "Accuracy", "model": "Pythia v0.3 (Ours)", "row": 11, "task": "Visual Question Answering", "value": "54.72" } ] }, { "index": 2, "records": [ { "column": 2, "dataset": "TextVQA Val", "metric": "Accuracy", "model": "Pythia + LoRRA", "row": 8, "task": "Visual Question Answering", "value": "26.56" }, { "column": 3, "dataset": "TextVQA Test", "metric": "Accuracy", "model": "Pythia + LoRRA", "row": 8, "task": "Visual Question Answering", "value": "27.63" } ] } ]

[ { "index": 0, "records": [ { "column": 3, "dataset": "J-HMDB", "metric": "Accuracy (pose)", "model": "EHPI", "row": 3, "task": "Skeleton Based Action Recognition", "value": "65.5" }, { "column": 3, "dataset": "JHMDB (2D poses only)", "metric": "Average accuracy of 3 splits", "model": "EHPI", "row": 3, "task": "Skeleton Based Action Recognition", "value": "65.5" } ] } ]

[ { "index": 0, "records": [ { "column": 4, "dataset": "XNLI Chinese Dev", "metric": "Accuracy", "model": "ERNIE", "row": 2, "task": "Natural Language Inference", "value": "79.9" }, { "column": 5, "dataset": "XNLI Chinese", "metric": "Accuracy", "model": "ERNIE", "row": 2, "task": "Natural Language Inference", "value": "78.4" }, { "column": 4, "dataset": "LCQMC Dev", "metric": "Accuracy", "model": "ERNIE", "row": 3, "task": "Chinese Sentence Pair Classification", "value": "89.7" }, { "column": 5, "dataset": "LCQMC", "metric": "Accuracy", "model": "ERNIE", "row": 3, "task": "Chinese Sentence Pair Classification", "value": "87.4" }, { "column": 4, "dataset": "MSRA Dev", "metric": "F1", "model": "ERNIE", "row": 4, "task": "Chinese Named Entity Recognition", "value": "95" }, { "column": 5, "dataset": "MSRA", "metric": "F1", "model": "ERNIE", "row": 4, "task": "Chinese Named Entity Recognition", "value": "93.8" }, { "column": 4, "dataset": "ChnSentiCorp Dev", "metric": "Accuracy", "model": "ERNIE", "row": 5, "task": "Chinese Sentiment Analysis", "value": "95.2" }, { "column": 5, "dataset": "ChnSentiCorp", "metric": "Accuracy", "model": "ERNIE", "row": 5, "task": "Chinese Sentiment Analysis", "value": "95.4" }, { "column": 4, "dataset": "NLPCC-DBQA Dev", "metric": "MRR", "model": "ERNIE", "row": 6, "task": "Chinese Sentence Pair Classification", "value": "0.95" }, { "column": 5, "dataset": "NLPCC-DBQA", "metric": "MRR", "model": "ERNIE", "row": 6, "task": "Chinese Sentence Pair Classification", "value": "0.951" }, { "column": 4, "dataset": "NLPCC-DBQA Dev", "metric": "F1", "model": "ERNIE", "row": 7, "task": "Chinese Sentence Pair Classification", "value": "82.3" }, { "column": 5, "dataset": "NLPCC-DBQA", "metric": "F1", "model": "ERNIE", "row": 7, "task": "Chinese Sentence Pair Classification", "value": "82.7" } ] } ]

[ { "index": 0, "records": [ { "column": 1, "dataset": "NIH", "metric": "Recall", "model": "U-Net+R+A4", "row": 34, "task": "Lung Nodule Segmentation", "value": "0.956" }, { "column": 2, "dataset": "NIH", "metric": "Precision", "model": "U-Net+R+A4", "row": 34, "task": "Lung Nodule Segmentation", "value": "0.969" }, { "column": 3, "dataset": "NIH", "metric": "Dice Score", "model": "U-Net+R+A4", "row": 34, "task": "Lung Nodule Segmentation", "value": "0.962" }, { "column": 4, "dataset": "NIH", "metric": "AVD", "model": "U-Net+R+A4", "row": 34, "task": "Lung Nodule Segmentation", "value": "0.262" }, { "column": 5, "dataset": "NIH", "metric": "VS", "model": "U-Net+R+A4", "row": 34, "task": "Lung Nodule Segmentation", "value": "0.985" } ] } ]

[ { "index": 2, "records": [ { "column": 3, "dataset": "UCF101-24", "metric": "Video-mAP 0.1", "model": "STEP", "row": 9, "task": "Action Detection", "value": "83.1" }, { "column": 4, "dataset": "UCF101-24", "metric": "Video-mAP 0.2", "model": "STEP", "row": 9, "task": "Action Detection", "value": "76.6" } ] } ]

[ { "index": 2, "records": [ { "column": 3, "dataset": "ECSSD", "metric": "F-measure", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.945" }, { "column": 4, "dataset": "ECSSD", "metric": "MAE", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.038" }, { "column": 5, "dataset": "PASCAL-S", "metric": "F-measure", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.88" }, { "column": 6, "dataset": "PASCAL-S", "metric": "MAE", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.065" }, { "column": 7, "dataset": "DUT-OMRON", "metric": "F-measure", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.833" }, { "column": 8, "dataset": "DUT-OMRON", "metric": "MAE", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.053" }, { "column": 9, "dataset": "HKU-IS", "metric": "F-measure", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.935" }, { "column": 10, "dataset": "HKU-IS", "metric": "MAE", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.03" }, { "column": 11, "dataset": "SOD", "metric": "F-measure", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.882" }, { "column": 12, "dataset": "SOD", "metric": "MAE", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.102" }, { "column": 13, "dataset": "DUTS-TE", "metric": "F-measure", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.892" }, { "column": 14, "dataset": "DUTS-TE", "metric": "MAE", "model": "PoolNet (VGG-16)", "row": 23, "task": "Salient Object Detection", "value": "0.036000000000000004" } ] } ]

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