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 ⌀ |
|---|---|---|---|---|---|
Facial Recognition and Modelling > Face Alignment | WFLW | LDDMM-Face | https://arxiv.org/abs/2108.00690v1 | NME (inter-ocular) | 4.63 |
Facial Recognition and Modelling > Face Alignment | WFLW | LDDMM-Face | https://arxiv.org/abs/2108.00690v1 | AUC@10 (inter-ocular) | 55.09 |
Facial Recognition and Modelling > Face Alignment | WFLW | LDDMM-Face | https://arxiv.org/abs/2108.00690v1 | FR@10 (inter-ocular) | 3.68 |
Facial Recognition and Modelling > Face Alignment | WFLW | GRegNet + LRefNet | http://openaccess.thecvf.com/content_CVPRW_2019/html/AMFG/Su_Efficient_and_Accurate_Face_Alignment_by_Global_Regression_and_Cascaded_CVPRW_2019_paper.html | NME (inter-ocular) | 4.65 |
Facial Recognition and Modelling > Face Alignment | WFLW | GRegNet + LRefNet | http://openaccess.thecvf.com/content_CVPRW_2019/html/AMFG/Su_Efficient_and_Accurate_Face_Alignment_by_Global_Regression_and_Cascaded_CVPRW_2019_paper.html | AUC@10 (inter-ocular) | 58.4 |
Facial Recognition and Modelling > Face Alignment | WFLW | GRegNet + LRefNet | http://openaccess.thecvf.com/content_CVPRW_2019/html/AMFG/Su_Efficient_and_Accurate_Face_Alignment_by_Global_Regression_and_Cascaded_CVPRW_2019_paper.html | FR@10 (inter-ocular) | 4.88 |
Facial Recognition and Modelling > Face Alignment | WFLW | 3DDE | https://arxiv.org/abs/1902.01831v2 | NME (inter-ocular) | 4.68 |
Facial Recognition and Modelling > Face Alignment | WFLW | 3DDE | https://arxiv.org/abs/1902.01831v2 | AUC@10 (inter-ocular) | 55.44 |
Facial Recognition and Modelling > Face Alignment | WFLW | 3DDE | https://arxiv.org/abs/1902.01831v2 | FR@10 (inter-ocular) | 5.04 |
Facial Recognition and Modelling > Face Alignment | WFLW | Wing | http://arxiv.org/abs/1711.06753v5 | NME (inter-ocular) | 5.11 |
Facial Recognition and Modelling > Face Alignment | WFLW | Wing | http://arxiv.org/abs/1711.06753v5 | AUC@10 (inter-ocular) | 55.4 |
Facial Recognition and Modelling > Face Alignment | WFLW | Wing | http://arxiv.org/abs/1711.06753v5 | FR@10 (inter-ocular) | 6.00 |
Facial Recognition and Modelling > Face Alignment | WFLW | ATPN | https://arxiv.org/abs/2103.07615v3 | NME (inter-ocular) | 5.13 |
Facial Recognition and Modelling > Face Alignment | WFLW | ATPN | https://arxiv.org/abs/2103.07615v3 | AUC@10 (inter-ocular) | 55.7 |
Facial Recognition and Modelling > Face Alignment | WFLW | ATPN | https://arxiv.org/abs/2103.07615v3 | FR@10 (inter-ocular) | 6.27 |
Facial Recognition and Modelling > Face Alignment | WFLW | LAB | http://arxiv.org/abs/1805.10483v1 | NME (inter-ocular) | 5.27 |
Facial Recognition and Modelling > Face Alignment | WFLW | LAB | http://arxiv.org/abs/1805.10483v1 | AUC@10 (inter-ocular) | 53.2 |
Facial Recognition and Modelling > Face Alignment | WFLW | LAB | http://arxiv.org/abs/1805.10483v1 | FR@10 (inter-ocular) | 7.56 |
Facial Recognition and Modelling > Face Alignment | WFLW | SCAF | https://link.springer.com/chapter/10.1007/978-3-031-06427-2_36 | NME (inter-ocular) | 5.50 |
Facial Recognition and Modelling > Face Alignment | WFLW | CFSS | https://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html | NME (inter-ocular) | 9.07 |
Facial Recognition and Modelling > Face Alignment | WFLW | CFSS | https://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html | AUC@10 (inter-ocular) | 36.6 |
Facial Recognition and Modelling > Face Alignment | WFLW | CFSS | https://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html | FR@10 (inter-ocular) | 20.56 |
Facial Recognition and Modelling > Face Alignment | WFLW | MobileNetV2 | https://arxiv.org/abs/2103.00119v3 | NME (inter-ocular) | 9.41 |
Facial Recognition and Modelling > Face Alignment | WFLW | SDM | http://openaccess.thecvf.com/content_cvpr_2013/html/Xiong_Supervised_Descent_Method_2013_CVPR_paper.html | NME (inter-ocular) | 10.29 |
Facial Recognition and Modelling > Face Alignment | WFLW | SDM | http://openaccess.thecvf.com/content_cvpr_2013/html/Xiong_Supervised_Descent_Method_2013_CVPR_paper.html | AUC@10 (inter-ocular) | 30.02 |
Facial Recognition and Modelling > Face Alignment | WFLW | SDM | http://openaccess.thecvf.com/content_cvpr_2013/html/Xiong_Supervised_Descent_Method_2013_CVPR_paper.html | FR@10 (inter-ocular) | 29.40 |
Facial Recognition and Modelling > Face Alignment | WFLW | ASMNet | https://arxiv.org/abs/2103.00119v3 | NME (inter-ocular) | 10.77 |
Facial Recognition and Modelling > Face Alignment | WFLW | DVLN | http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/html/Wu_Leveraging_Intra_and_CVPR_2017_paper.html | NME (inter-ocular) | 10.84 |
Facial Recognition and Modelling > Face Alignment | WFLW | DVLN | http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/html/Wu_Leveraging_Intra_and_CVPR_2017_paper.html | AUC@10 (inter-ocular) | 45.6 |
Facial Recognition and Modelling > Face Alignment | WFLW | DVLN | http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/html/Wu_Leveraging_Intra_and_CVPR_2017_paper.html | FR@10 (inter-ocular) | 10.84 |
Facial Recognition and Modelling > Face Alignment | WFLW | ESR | https://ieeexplore.ieee.org/document/6248015 | NME (inter-ocular) | 11.13 |
Facial Recognition and Modelling > Face Alignment | WFLW | ESR | https://ieeexplore.ieee.org/document/6248015 | AUC@10 (inter-ocular) | 27.74 |
Facial Recognition and Modelling > Face Alignment | WFLW | ESR | https://ieeexplore.ieee.org/document/6248015 | FR@10 (inter-ocular) | 35.24 |
Facial Recognition and Modelling > Face Alignment | CelebA + AFLW Unaligned | Progressive Face SR | https://arxiv.org/abs/1908.08239v1 | MOS | 3.73 |
Facial Recognition and Modelling > Face Alignment | CelebA + AFLW Unaligned | Progressive Face SR | https://arxiv.org/abs/1908.08239v1 | MS-SSIM | 0.897 |
Facial Recognition and Modelling > Face Alignment | CelebA + AFLW Unaligned | Progressive Face SR | https://arxiv.org/abs/1908.08239v1 | PSNR | 22.96 |
Facial Recognition and Modelling > Face Alignment | CelebA + AFLW Unaligned | Progressive Face SR | https://arxiv.org/abs/1908.08239v1 | SSIM | 0.695 |
Facial Recognition and Modelling > Face Alignment | AFLW-PIFA (21 points) | Face alignment | https://www.adrianbulat.com/downloads/BMVC16/cale_bmvc16.pdf | NME | 2.63% |
Facial Recognition and Modelling > Face Alignment | AFLW-Full | Binary Face Alignment | http://arxiv.org/abs/1703.00862v2 | Mean NME | 2.85 |
Facial Recognition and Modelling > Face Alignment | AFLW-Full | AnchorFace | https://arxiv.org/abs/2007.03221v3 | Mean NME | 1.56 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | SPIGA | https://arxiv.org/abs/2210.07233v1 | NME (box) | 2.03 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | SPIGA | https://arxiv.org/abs/2210.07233v1 | AUC@7 (box) | 71.0 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | SPIGA | https://arxiv.org/abs/2210.07233v1 | NME (inter-ocular) | 3.43 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | SPIGA | https://arxiv.org/abs/2210.07233v1 | AUC@8 (inter-ocular) | 57.27 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | SPIGA | https://arxiv.org/abs/2210.07233v1 | FR@8 (inter-ocular) | 0.67 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | DTLD-s | https://arxiv.org/abs/2208.10808v1 | NME (box) | 2.05 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | DTLD-s | https://arxiv.org/abs/2208.10808v1 | AUC@7 (box) | 70.9 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | LUVLi | https://arxiv.org/abs/2004.02980v1 | NME (box) | 2.24 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | LUVLi | https://arxiv.org/abs/2004.02980v1 | AUC@7 (box) | 68.3 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | KDN | http://openaccess.thecvf.com/content_ICCV_2019/html/Chen_Face_Alignment_With_Kernel_Density_Deep_Neural_Network_ICCV_2019_paper.html | NME (box) | 2.49 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | KDN | http://openaccess.thecvf.com/content_ICCV_2019/html/Chen_Face_Alignment_With_Kernel_Density_Deep_Neural_Network_ICCV_2019_paper.html | AUC@7 (box) | 67.3 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | 3DDE | https://arxiv.org/abs/1902.01831v2 | NME (inter-ocular) | 3.73 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | 3DDE | https://arxiv.org/abs/1902.01831v2 | AUC@8 (inter-ocular) | 53.94 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | 3DDE | https://arxiv.org/abs/1902.01831v2 | FR@8 (inter-ocular) | 2.33 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | DCFE | http://openaccess.thecvf.com/content_ECCV_2018/html/Roberto_Valle_A_Deeply-initialized_Coarse-to-fine_ECCV_2018_paper.html | NME (inter-ocular) | 3.88 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | DCFE | http://openaccess.thecvf.com/content_ECCV_2018/html/Roberto_Valle_A_Deeply-initialized_Coarse-to-fine_ECCV_2018_paper.html | AUC@8 (inter-ocular) | 52.42 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | DCFE | http://openaccess.thecvf.com/content_ECCV_2018/html/Roberto_Valle_A_Deeply-initialized_Coarse-to-fine_ECCV_2018_paper.html | FR@8 (inter-ocular) | 1.83 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | DAN | http://arxiv.org/abs/1706.01789v2 | NME (inter-ocular) | 4.30 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | DAN | http://arxiv.org/abs/1706.01789v2 | AUC@8 (inter-ocular) | 47.00 |
Facial Recognition and Modelling > Face Alignment | 300W Split 2 | DAN | http://arxiv.org/abs/1706.01789v2 | FR@8 (inter-ocular) | 2.67 |
Facial Recognition and Modelling > Face Alignment | AFLW2000 | MNN+ORB (Reannotated) | https://arxiv.org/abs/2202.02299v1 | Error rate | 2.58 |
Facial Recognition and Modelling > Face Alignment | AFLW2000 | Nonlinear 3D Face Morphable Model | http://arxiv.org/abs/1804.03786v3 | Error rate | 4.70 |
Facial Recognition and Modelling > Face Alignment | AFLW2000 | MCL | http://arxiv.org/abs/1808.01558v2 | Error rate | 5.38 |
Facial Recognition and Modelling > Face Alignment | AFLW2000 | 3DDFA | http://arxiv.org/abs/1511.07212v1 | Error rate | 5.42 |
Facial Recognition and Modelling > Face Alignment | AFLW2000 | Dlib (68 points) | http://openaccess.thecvf.com/content_cvpr_2014/html/Kazemi_One_Millisecond_Face_2014_CVPR_paper.html | Error rate | 10.545 |
Facial Recognition and Modelling > Face Alignment | IBUG | DenseU-Net + Dual Transformer | http://arxiv.org/abs/1812.01936v1 | Mean Error Rate | 6.73% |
Facial Recognition and Modelling > Face Alignment | IBUG | DCFE (inter pupils normalization) | http://openaccess.thecvf.com/content_ECCV_2018/html/Roberto_Valle_A_Deeply-initialized_Coarse-to-fine_ECCV_2018_paper.html | Mean Error Rate | 7.54% |
Facial Recognition and Modelling > Face Alignment | FaceScape | ASM | https://arxiv.org/abs/2304.09423v3 | NME | 0.21 |
Facial Recognition and Modelling > Face Alignment | FaceScape | ImFace | https://arxiv.org/abs/2203.14510v2 | NME | 0.257 |
Facial Recognition and Modelling > Face Alignment | FaceScape | FLAME | http://flame.is.tue.mpg.de/ | NME | 0.341 |
Facial Recognition and Modelling > Face Alignment | FaceScape | CoMA | http://arxiv.org/abs/1807.10267v3 | NME | 1.088 |
Facial Recognition and Modelling > Face Alignment | AFLW-LFPA | FPN | http://arxiv.org/abs/1803.07835v1 | Mean NME | 2.93% |
Facial Recognition and Modelling > Face Alignment | AFLW-LFPA | DeFA | http://arxiv.org/abs/1709.01442v1 | Mean NME | 3.86% |
Facial Recognition and Modelling > Face Alignment | AFLW-LFPA | Ours | http://arxiv.org/abs/1808.04803v1 | NME | 3.02 |
Facial Recognition and Modelling > Age Estimation | LAGENDA | MiVOLO-V2 | https://arxiv.org/abs/2403.02302v4 | MAE | 3.65 |
Facial Recognition and Modelling > Age Estimation | LAGENDA | MiVOLO-D1 | https://arxiv.org/abs/2307.04616v2 | MAE | 3.99 |
Facial Recognition and Modelling > Age Estimation | AgeDB | MiVOLO-D1 | https://arxiv.org/abs/2307.04616v2 | MAE | 5.55 |
Facial Recognition and Modelling > Age Estimation | AgeDB | FaRL+MLP | https://arxiv.org/abs/2307.04570v3 | MAE | 5.64 |
Facial Recognition and Modelling > Age Estimation | AgeDB | ResNet-50-OR-CNN | https://arxiv.org/abs/2307.04570v3 | MAE | 5.78 |
Facial Recognition and Modelling > Age Estimation | AgeDB | ResNet-50-DLDL | https://arxiv.org/abs/2307.04570v3 | MAE | 5.80 |
Facial Recognition and Modelling > Age Estimation | AgeDB | ResNet-50-DLDL-v2 | https://arxiv.org/abs/2307.04570v3 | MAE | 5.80 |
Facial Recognition and Modelling > Age Estimation | AgeDB | ResNet-50-Cross-Entropy | https://arxiv.org/abs/2307.04570v3 | MAE | 5.81 |
Facial Recognition and Modelling > Age Estimation | AgeDB | ResNet-50-SORD | https://arxiv.org/abs/2307.04570v3 | MAE | 5.81 |
Facial Recognition and Modelling > Age Estimation | AgeDB | ResNet-50-Mean-Variance | https://arxiv.org/abs/2307.04570v3 | MAE | 5.85 |
Facial Recognition and Modelling > Age Estimation | AgeDB | ResNet-50-Unimodal-Concentrated | https://arxiv.org/abs/2307.04570v3 | MAE | 5.90 |
Facial Recognition and Modelling > Age Estimation | AgeDB | ResNet-50-Regression | https://arxiv.org/abs/2307.04570v3 | MAE | 6.23 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | MWR | https://arxiv.org/abs/2203.13122v1 | MAE | 2.13 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | MetaAge | https://arxiv.org/abs/2207.05288v1 | MAE | 2.23 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | DRC-ORID | https://openreview.net/forum?id=Yz-XtK5RBxB | MAE | 2.26 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | OrdinalCLIP | https://arxiv.org/abs/2206.02338v2 | MAE | 2.32 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | POE | https://arxiv.org/abs/2103.13629v1 | MAE | 2.35 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | AVDL | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4328_ECCV_2020_paper.php | MAE | 2.37 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | BridgeNet | http://arxiv.org/abs/1904.03358v1 | MAE | 2.38 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | OL | https://openreview.net/forum?id=HygsuaNFwr | MAE | 2.41 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | DEX | https://link.springer.com/article/10.1007/s11263-016-0940-3 | MAE | 2.68 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | DRFs | http://arxiv.org/abs/1712.07195v1 | MAE | 2.91 |
Facial Recognition and Modelling > Age Estimation | MORPH album2 (Caucasian) | dLDLF | http://arxiv.org/abs/1702.06086v4 | MAE | 3.02 |
Facial Recognition and Modelling > Age Estimation | AFAD | CORAL | https://arxiv.org/abs/1901.07884v7 | MAE | 3.48 |
Facial Recognition and Modelling > Age Estimation | AFAD | ResNet-50-Unimodal-Concentrated | https://arxiv.org/abs/2307.04570v3 | MAE | 3.20 |
Facial Recognition and Modelling > Age Estimation | AFAD | ResNet-50-Regression | https://arxiv.org/abs/2307.04570v3 | MAE | 3.17 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.