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 ⌀ |
|---|---|---|---|---|---|
Keyword Spotting | QUESST | TUKE g-U (dev) | http://ceur-ws.org/Vol-1436/Paper45.pdf | PMUi | 0.515 |
Keyword Spotting | QUESST | TUKE g-U (dev) | http://ceur-ws.org/Vol-1436/Paper45.pdf | PL | 0.033 |
Keyword Spotting | QUESST | TUKE g-U late submission (eval) | http://ceur-ws.org/Vol-1436/Paper45.pdf | Cnxe | 0.974 |
Keyword Spotting | QUESST | TUKE g-U late submission (eval) | http://ceur-ws.org/Vol-1436/Paper45.pdf | MinCnxe | 0.954 |
Keyword Spotting | QUESST | TUKE g-U late submission (eval) | http://ceur-ws.org/Vol-1436/Paper45.pdf | ATWV | 0.028 |
Keyword Spotting | QUESST | TUKE g-U late submission (eval) | http://ceur-ws.org/Vol-1436/Paper45.pdf | MTWV | 0.032 |
Keyword Spotting | QUESST | GTM-UVigo Contrastive late submission (eval) | http://ceur-ws.org/Vol-1436/Paper52.pdf | Cnxe | 0.989 |
Keyword Spotting | QUESST | GTM-UVigo Contrastive late submission (eval) | http://ceur-ws.org/Vol-1436/Paper52.pdf | MinCnxe | 0.852 |
Keyword Spotting | QUESST | GTM-UVigo Contrastive late submission (eval) | http://ceur-ws.org/Vol-1436/Paper52.pdf | lowerbound | 0.613 |
Keyword Spotting | QUESST | GTM-UVigo Contrastive (dev) | http://ceur-ws.org/Vol-1436/Paper52.pdf | Cnxe | 0.998 |
Keyword Spotting | QUESST | GTM-UVigo Contrastive (dev) | http://ceur-ws.org/Vol-1436/Paper52.pdf | MinCnxe | 0.918 |
Keyword Spotting | QUESST | GTM-UVigo Contrastive (dev) | http://ceur-ws.org/Vol-1436/Paper52.pdf | lowerbound | 0.635 |
Keyword Spotting | QUESST | CUNY [SMO+iSAX] (dev) | http://ceur-ws.org/Vol-1436/Paper83.pdf | Cnxe | 0.9988 |
Keyword Spotting | QUESST | CUNY [SMO+iSAX] (dev) | http://ceur-ws.org/Vol-1436/Paper83.pdf | MinCnxe | 0.9872 |
Keyword Spotting | QUESST | CUNY [SMO+iSAX] (dev) | http://ceur-ws.org/Vol-1436/Paper83.pdf | ATWV | 0.0011 |
Keyword Spotting | QUESST | CUNY [SMO+iSAX] (dev) | http://ceur-ws.org/Vol-1436/Paper83.pdf | MTWV | 0.0067 |
Keyword Spotting | QUESST | CUNY [SMO+iSAX] (eval) | http://ceur-ws.org/Vol-1436/Paper83.pdf | Cnxe | 0.9989 |
Keyword Spotting | QUESST | CUNY [SMO+iSAX] (eval) | http://ceur-ws.org/Vol-1436/Paper83.pdf | MinCnxe | 0.9870 |
Keyword Spotting | QUESST | CUNY [SMO+iSAX] (eval) | http://ceur-ws.org/Vol-1436/Paper83.pdf | ATWV | 0.0006 |
Keyword Spotting | QUESST | CUNY [SMO+iSAX] (eval) | http://ceur-ws.org/Vol-1436/Paper83.pdf | MTWV | 0.0010 |
Keyword Spotting | QUESST | GTM-UVigo Contrastive (eval) | http://ceur-ws.org/Vol-1436/Paper52.pdf | Cnxe | 0.999 |
Keyword Spotting | QUESST | GTM-UVigo Contrastive (eval) | http://ceur-ws.org/Vol-1436/Paper52.pdf | MinCnxe | 0.923 |
Keyword Spotting | QUESST | GTM-UVigo Contrastive (eval) | http://ceur-ws.org/Vol-1436/Paper52.pdf | lowerbound | 0.633 |
Keyword Spotting | QUESST | ELiRF SDTW-avg (dev) | http://ceur-ws.org/Vol-1436/Paper48.pdf | Cnxe | 1.0651 |
Keyword Spotting | QUESST | ELiRF SDTW-avg (dev) | http://ceur-ws.org/Vol-1436/Paper48.pdf | MinCnxe | 0.8677 |
Keyword Spotting | QUESST | ELiRF SDTW-avg (dev) | http://ceur-ws.org/Vol-1436/Paper48.pdf | ATWV | 0.1446 |
Keyword Spotting | QUESST | ELiRF SDTW-avg (dev) | http://ceur-ws.org/Vol-1436/Paper48.pdf | MTWV | 0.1543 |
Keyword Spotting | QUESST | CUNY [Subseq+MFCC] (dev) | http://ceur-ws.org/Vol-1436/Paper83.pdf | Cnxe | 1.0658 |
Keyword Spotting | QUESST | CUNY [Subseq+MFCC] (dev) | http://ceur-ws.org/Vol-1436/Paper83.pdf | MinCnxe | 0.9823 |
Keyword Spotting | QUESST | CUNY [Subseq+MFCC] (dev) | http://ceur-ws.org/Vol-1436/Paper83.pdf | ATWV | -3.9820 |
Keyword Spotting | QUESST | CUNY [Subseq+MFCC] (dev) | http://ceur-ws.org/Vol-1436/Paper83.pdf | MTWV | 0.0123 |
Keyword Spotting | QUESST | CUNY [Subseq+MFCC] (eval) | http://ceur-ws.org/Vol-1436/Paper83.pdf | Cnxe | 1.0674 |
Keyword Spotting | QUESST | CUNY [Subseq+MFCC] (eval) | http://ceur-ws.org/Vol-1436/Paper83.pdf | MinCnxe | 0.9853 |
Keyword Spotting | QUESST | CUNY [Subseq+MFCC] (eval) | http://ceur-ws.org/Vol-1436/Paper83.pdf | ATWV | -4.0205 |
Keyword Spotting | QUESST | CUNY [Subseq+MFCC] (eval) | http://ceur-ws.org/Vol-1436/Paper83.pdf | MTWV | 0.0006 |
Keyword Spotting | QUESST | ELiRF SDTW (dev) | http://ceur-ws.org/Vol-1436/Paper48.pdf | Cnxe | 1.0701 |
Keyword Spotting | QUESST | ELiRF SDTW (dev) | http://ceur-ws.org/Vol-1436/Paper48.pdf | MinCnxe | 0.8702 |
Keyword Spotting | QUESST | ELiRF SDTW (dev) | http://ceur-ws.org/Vol-1436/Paper48.pdf | ATWV | 0.1404 |
Keyword Spotting | QUESST | ELiRF SDTW (dev) | http://ceur-ws.org/Vol-1436/Paper48.pdf | MTWV | 0.1493 |
Keyword Spotting | QUESST | ELiRF SDTW-avg (eval) | http://ceur-ws.org/Vol-1436/Paper48.pdf | Cnxe | 1.0731 |
Keyword Spotting | QUESST | ELiRF SDTW-avg (eval) | http://ceur-ws.org/Vol-1436/Paper48.pdf | MinCnxe | 0.8751 |
Keyword Spotting | QUESST | ELiRF SDTW-avg (eval) | http://ceur-ws.org/Vol-1436/Paper48.pdf | ATWV | 0.1125 |
Keyword Spotting | QUESST | ELiRF SDTW-avg (eval) | http://ceur-ws.org/Vol-1436/Paper48.pdf | MTWV | 0.1181 |
Keyword Spotting | QUESST | ELiRF SDTW (eval) | http://ceur-ws.org/Vol-1436/Paper48.pdf | Cnxe | 1.1879 |
Keyword Spotting | QUESST | ELiRF SDTW (eval) | http://ceur-ws.org/Vol-1436/Paper48.pdf | MinCnxe | 0.9338 |
Keyword Spotting | QUESST | ELiRF SDTW (eval) | http://ceur-ws.org/Vol-1436/Paper48.pdf | ATWV | 0.0449 |
Keyword Spotting | QUESST | ELiRF SDTW (eval) | http://ceur-ws.org/Vol-1436/Paper48.pdf | MTWV | 0.0581 |
Keyword Spotting | QUESST | NTU dtw (dev) | http://ceur-ws.org/Vol-1436/Paper74.pdf | Cnxe | 2.0066 |
Keyword Spotting | QUESST | NTU rnn (dev) | http://ceur-ws.org/Vol-1436/Paper74.pdf | Cnxe | 2.0066 |
Keyword Spotting | QUESST | NTU dtw (eval) | http://ceur-ws.org/Vol-1436/Paper74.pdf | Cnxe | 2.0067 |
Keyword Spotting | QUESST | NTU rnn (eval) | http://ceur-ws.org/Vol-1436/Paper74.pdf | Cnxe | 2.0067 |
Keyword Spotting | QUESST | NNI Choi(for the development set) | http://www.npu-aslp.org/lxie/papers/2014QUESST-NNI.pdf | Cnxe | 5.8940 |
Keyword Spotting | QUESST | NNI Choi(for the development set) | http://www.npu-aslp.org/lxie/papers/2014QUESST-NNI.pdf | MinCnxe | 0.9595 |
Keyword Spotting | QUESST | NNI Choi(for the development set) | http://www.npu-aslp.org/lxie/papers/2014QUESST-NNI.pdf | ATWV | 0.0692 |
Keyword Spotting | QUESST | NNI Choi(for the development set) | http://www.npu-aslp.org/lxie/papers/2014QUESST-NNI.pdf | MTWV | 0.0692 |
Keyword Spotting | QUESST | NNI non-filtered(for the development set) | http://www.npu-aslp.org/lxie/papers/2014QUESST-NNI.pdf | Cnxe | 6.0905 |
Keyword Spotting | QUESST | NNI non-filtered(for the development set) | http://www.npu-aslp.org/lxie/papers/2014QUESST-NNI.pdf | MinCnxe | 0.9571 |
Keyword Spotting | QUESST | NNI non-filtered(for the development set) | http://www.npu-aslp.org/lxie/papers/2014QUESST-NNI.pdf | ATWV | 0.0768 |
Keyword Spotting | QUESST | NNI non-filtered(for the development set) | http://www.npu-aslp.org/lxie/papers/2014QUESST-NNI.pdf | MTWV | 0.0767 |
Keyword Spotting | QUESST | BUT (p-bigfusion) | http://ceur-ws.org/Vol-1263/mediaeval2014_submission_62.pdf | MinCnxe | 0.461 |
Keyword Spotting | QUESST | BUT (g-bigfusionnoside ) | http://ceur-ws.org/Vol-1263/mediaeval2014_submission_62.pdf | MinCnxe | 0.486 |
Keyword Spotting | QUESST | BUT (g-best_single) | http://ceur-ws.org/Vol-1263/mediaeval2014_submission_62.pdf | MinCnxe | 0.533 |
Keyword Spotting | QUESST | BUT (AKWS-cz) | http://ceur-ws.org/Vol-1263/mediaeval2014_submission_62.pdf | MinCnxe | 0.641 |
Keyword Spotting | QUESST | BUT (AKWS-T3-cz) | http://ceur-ws.org/Vol-1263/mediaeval2014_submission_62.pdf | MinCnxe | 0.673 |
Keyword Spotting | QUESST | BUT (g-LID) | http://ceur-ws.org/Vol-1263/mediaeval2014_submission_62.pdf | MinCnxe | 0.929 |
Keyword Spotting | Google Speech Commands V2 12 | MicroNet-KWS-L | https://arxiv.org/abs/2010.11267v6 | Accuracy | 95.3 |
Keyword Spotting | Google Speech Commands V2 12 | MicroNet-KWS-L | https://arxiv.org/abs/2010.11267v6 | Latency (STM32F746ZG) | 0.610128 |
Keyword Spotting | FKD | Res26 | https://arxiv.org/abs/2012.15695v1 | Accuracy | 95.88 |
Keyword Spotting | FKD | EfficientNet-A0 + SA + TL | https://arxiv.org/abs/2012.15695v1 | Accuracy | 95.83 |
Keyword Spotting | hey Siri | HEiMDaL | https://arxiv.org/abs/2210.15425v1 | Error Rate | 0.45% |
Keyword Spotting | hey Siri | End-to-end DNN-HMM | https://arxiv.org/abs/2011.01151v2 | Error Rate | 1.7% |
Keyword Spotting | hey Siri | End-to-end DNN-HMM | https://arxiv.org/abs/2210.15425v1 | Error Rate | 1.7% |
Keyword Spotting | hey Siri | Stacked 1D CNN | https://arxiv.org/abs/2210.15425v1 | Error Rate | 1.99% |
Keyword Spotting | Google Speech Commands V2 35 | QuaternionNeuralNetwork | https://ieeexplore.ieee.org/document/10248052 | Accuracy (10-fold) | 98.53 |
Keyword Spotting | Google Speech Commands V2 35 | SSAMBA | https://arxiv.org/abs/2405.11831v2 | Accuracy (10-fold) | 97.4 |
Keyword Spotting > Visual Keyword Spotting | LRS3-TED | Transpotter | https://arxiv.org/abs/2110.15957v1 | Top-1 Accuracy | 52 |
Keyword Spotting > Visual Keyword Spotting | LRS3-TED | Transpotter | https://arxiv.org/abs/2110.15957v1 | Top-5 Accuracy | 77.1 |
Keyword Spotting > Visual Keyword Spotting | LRS3-TED | Transpotter | https://arxiv.org/abs/2110.15957v1 | mAP | 55.4 |
Keyword Spotting > Visual Keyword Spotting | LRS3-TED | Transpotter | https://arxiv.org/abs/2110.15957v1 | mAP IOU@0.5 | 53.6 |
Keyword Spotting > Visual Keyword Spotting | LRS2 | Transpotter | https://arxiv.org/abs/2110.15957v1 | Top-1 Accuracy | 65 |
Keyword Spotting > Visual Keyword Spotting | LRS2 | Transpotter | https://arxiv.org/abs/2110.15957v1 | Top-5 Accuracy | 87.1 |
Keyword Spotting > Visual Keyword Spotting | LRS2 | Transpotter | https://arxiv.org/abs/2110.15957v1 | mAP | 69.2 |
Keyword Spotting > Visual Keyword Spotting | LRS2 | Transpotter | https://arxiv.org/abs/2110.15957v1 | mAP IOU@0.5 | 68.3 |
Keyword Spotting > Visual Keyword Spotting | LRW | Transpotter | https://arxiv.org/abs/2110.15957v1 | Top-1 Accuracy | 85.8 |
Keyword Spotting > Visual Keyword Spotting | LRW | Transpotter | https://arxiv.org/abs/2110.15957v1 | Top-5 Accuracy | 99.6 |
Keyword Spotting > Visual Keyword Spotting | LRW | Transpotter | https://arxiv.org/abs/2110.15957v1 | mAP | 64.1 |
3D Human Pose Estimation | HumanEva-I | GLA-GCN (T=27, GT) | https://arxiv.org/abs/2307.05853v2 | Mean Reconstruction Error (mm) | 9.2 |
3D Human Pose Estimation | HumanEva-I | StridedTransformer (T=27 GT) | https://arxiv.org/abs/2103.14304v8 | Mean Reconstruction Error (mm) | 12.2 |
3D Human Pose Estimation | HumanEva-I | Spatio-Temporal Network (T=128) | https://arxiv.org/abs/2004.11822v1 | Mean Reconstruction Error (mm) | 13.5 |
3D Human Pose Estimation | HumanEva-I | Occlusion-Aware Networks | http://openaccess.thecvf.com/content_ICCV_2019/html/Cheng_Occlusion-Aware_Networks_for_3D_Human_Pose_Estimation_in_Video_ICCV_2019_paper.html | Mean Reconstruction Error (mm) | 14.3 |
3D Human Pose Estimation | HumanEva-I | HEMlets Pose | https://arxiv.org/abs/1910.12032v1 | Mean Reconstruction Error (mm) | 15.2 |
3D Human Pose Estimation | HumanEva-I | Attention (T=27 MA) | https://arxiv.org/abs/2103.03170v1 | Mean Reconstruction Error (mm) | 15.4 |
3D Human Pose Estimation | HumanEva-I | MixSTE (T=43, FT) | https://arxiv.org/abs/2203.00859v4 | Mean Reconstruction Error (mm) | 16.1 |
3D Human Pose Estimation | HumanEva-I | Ordinal Depth Supervision | http://arxiv.org/abs/1805.04095v1 | Mean Reconstruction Error (mm) | 18.3 |
3D Human Pose Estimation | HumanEva-I | StridedTransformer (T=27 MRCNN) | https://arxiv.org/abs/2103.14304v8 | Mean Reconstruction Error (mm) | 18.9 |
3D Human Pose Estimation | HumanEva-I | RTPCA | https://arxiv.org/abs/2309.01365v3 | Mean Reconstruction Error (mm) | 19.1 |
3D Human Pose Estimation | HumanEva-I | DG-Net (T=4) | https://arxiv.org/abs/2109.07353v1 | Mean Reconstruction Error (mm) | 19.5 |
3D Human Pose Estimation | HumanEva-I | GAST | https://arxiv.org/abs/2003.14179v4 | Mean Reconstruction Error (mm) | 21.2 |
3D Human Pose Estimation | HumanEva-I | PoseFormer | https://arxiv.org/abs/2103.10455v3 | Mean Reconstruction Error (mm) | 21.6 |
3D Human Pose Estimation | HumanEva-I | Sequence-to-sequence network | http://arxiv.org/abs/1711.08585v4 | Mean Reconstruction Error (mm) | 22 |
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