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 > Facial Expression Recognition (FER) | AffectNet | DAN | https://arxiv.org/abs/2109.07270v6 | Accuracy (7 emotion) | 65.69 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | DAN | https://arxiv.org/abs/2109.07270v6 | Accuracy (8 emotion) | 62.09 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | SL + SSL in-panting-pl (B0) | https://arxiv.org/abs/2105.06421v3 | Accuracy (8 emotion) | 61.72 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Distilled student | https://arxiv.org/abs/2103.09154v2 | Accuracy (7 emotion) | 65.4 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Distilled student | https://arxiv.org/abs/2103.09154v2 | Accuracy (8 emotion) | 61.60 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Multi-task EfficientNet-B0 | https://arxiv.org/abs/2103.17107 | Accuracy (7 emotion) | 65.74 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Multi-task EfficientNet-B0 | https://arxiv.org/abs/2103.17107 | Accuracy (8 emotion) | 61.32 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | SL + SSL puzzling (B2) | https://arxiv.org/abs/2105.06421v3 | Accuracy (8 emotion) | 61.32 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | SL + SSL puzzling (B0) | https://arxiv.org/abs/2105.06421v3 | Accuracy (8 emotion) | 61.09 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | PSR (VGG-16) | https://doi.org/10.1109/ACCESS.2020.3010018 | Accuracy (7 emotion) | - |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | PSR (VGG-16) | https://doi.org/10.1109/ACCESS.2020.3010018 | Accuracy (8 emotion) | 60.68 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | VGG-FACE | https://arxiv.org/abs/1811.05027v2 | Accuracy (8 emotion) | 60.40 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | SL (B2) | https://arxiv.org/abs/2105.06421v3 | Accuracy (8 emotion) | 60.35 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | SL (B0) | https://arxiv.org/abs/2105.06421v3 | Accuracy (8 emotion) | 60.34 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | MA-Net | https://ieeexplore.ieee.org/document/9474949 | Accuracy (7 emotion) | 64.53 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | MA-Net | https://ieeexplore.ieee.org/document/9474949 | Accuracy (8 emotion) | 60.29 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | EfficientFace | https://ojs.aaai.org/index.php/AAAI/article/view/16465 | Accuracy (7 emotion) | 63.70 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | EfficientFace | https://ojs.aaai.org/index.php/AAAI/article/view/16465 | Accuracy (8 emotion) | 59.89 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | CNNs and BOVW + local SVM | https://arxiv.org/abs/1804.10892v7 | Accuracy (7 emotion) | 63.31 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | CNNs and BOVW + local SVM | https://arxiv.org/abs/1804.10892v7 | Accuracy (8 emotion) | 59.58 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | RAN (ResNet-18+) | https://arxiv.org/abs/1905.04075v2 | Accuracy (7 emotion) | - |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | RAN (ResNet-18+) | https://arxiv.org/abs/1905.04075v2 | Accuracy (8 emotion) | 59.5 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Ensemble with Shared Representations (ESR-9) | https://arxiv.org/abs/2001.06338v1 | Accuracy (7 emotion) | - |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Ensemble with Shared Representations (ESR-9) | https://arxiv.org/abs/2001.06338v1 | Accuracy (8 emotion) | 59.3 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | ViT-tiny | https://arxiv.org/abs/2207.11081v4 | Accuracy (8 emotion) | 58.28 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Weighted-Loss | http://arxiv.org/abs/1708.03985v4 | Accuracy (7 emotion) | - |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Weighted-Loss | http://arxiv.org/abs/1708.03985v4 | Accuracy (8 emotion) | 58.0 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | ViT-base | https://arxiv.org/abs/2207.11081v4 | Accuracy (8 emotion) | 57.99 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | SL+ SSL in-painting-pl + 20% train (B0) | https://arxiv.org/abs/2105.06421v3 | Accuracy (8 emotion) | 55.36 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | SL+ SSL puzzling + 20% train (B0) | https://arxiv.org/abs/2105.06421v3 | Accuracy (8 emotion) | 54.98 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | LResNet50E-IR | https://arxiv.org/abs/2012.13912v1 | Accuracy (8 emotion) | 53.925 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | SL + 20% train (B0) | https://arxiv.org/abs/2105.06421v3 | Accuracy (8 emotion) | 52.46 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | ResEmoteNet | https://arxiv.org/abs/2409.10545v2 | Accuracy (7 emotion) | 72.93 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | EmoAffectNet | https://www.sciencedirect.com/science/article/abs/pii/S0925231222012656 | Accuracy (7 emotion) | 66.49 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Emotion-GCN | https://arxiv.org/abs/2106.03487v2 | Accuracy (7 emotion) | 66.46 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | FaceBehaviorNet | https://arxiv.org/abs/2105.03790v1 | Accuracy (7 emotion) | 65.40 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Ada-DF | https://ieeexplore.ieee.org/document/10097033 | Accuracy (7 emotion) | 65.34 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | EAC | https://arxiv.org/abs/2207.10299v2 | Accuracy (7 emotion) | 65.32 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | PAENet | https://dl.acm.org/doi/10.1145/3323873.3325053 | Accuracy (7 emotion) | 65.29 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | DACL | https://openaccess.thecvf.com/content/WACV2021/html/Farzaneh_Facial_Expression_Recognition_in_the_Wild_via_Deep_Attentive_Center_WACV_2021_paper.html | Accuracy (7 emotion) | 65.20 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | FerNeXt | https://ieeexplore.ieee.org/document/10278345 | Accuracy (7 emotion) | 64.77 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | CPG | https://arxiv.org/abs/1910.06562v3 | Accuracy (7 emotion) | 63.57 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Ad-Corre | https://ieeexplore.ieee.org/document/9727163 | Accuracy (7 emotion) | 63.36 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | CAKE | http://arxiv.org/abs/1807.11215v2 | Accuracy (7 emotion) | 61.7 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | AffectNet | Facial Motion Prior Network | https://arxiv.org/abs/1902.08788v2 | Accuracy (7 emotion) | 61.52 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | FERPlus | KTN | https://doi.org/10.1109/TIP.2021.3049955 | Accuracy(pretrained) | 90.49 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | FERPlus | RAN (VGG-16) | https://arxiv.org/abs/1905.04075v2 | Accuracy(pretrained) | 89.16 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | FERPlus | SENet Teacher | http://arxiv.org/abs/1808.05561v1 | Accuracy(pretrained) | 88.88 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) | FERPlus | Local Learning Deep + BOW | https://arxiv.org/abs/1804.10892v7 | Accuracy(pretrained) | 87.76 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) > Micro-Expression Recognition | CASME II | HTNet | https://arxiv.org/abs/2307.14637v1 | UF1 | 95.32 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) > Micro-Expression Recognition | CASME II | HTNet | https://arxiv.org/abs/2307.14637v1 | UAR | 95.16 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) > 3D Facial Expression Recognition | 2017_test set | aan | http://arxiv.org/abs/1802.00542v1 | 14 gestures accuracy | 2 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) > 3D Facial Expression Recognition | !(()&&!|*|*| | nyenye | https://arxiv.org/abs/2206.09379v2 | 0L | 100 |
Facial Recognition and Modelling > Facial Expression Recognition (FER) > Smile Recognition | DISFA | Deep CNN | http://arxiv.org/abs/1602.00172v2 | Accuracy | 99.45% |
Facial Recognition and Modelling > Face Detection | Manga109 | DASS-Detector (YOLOX XL) | https://arxiv.org/abs/2211.10641v2 | Average Precision | 87.88 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | ASFD-D6 | https://arxiv.org/abs/2201.10781v1 | AP | 0.965 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | RetinaFace+Lpts+Lpixel | https://arxiv.org/abs/1905.00641v2 | AP | 0.96175 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | Poly-NL(ResNet-50) | https://arxiv.org/abs/2107.02859v1 | AP | 0.9571 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | AInnoFace | https://arxiv.org/abs/1905.01585v3 | AP | 0.957 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | DSFD | http://arxiv.org/abs/1810.10220v3 | AP | 0.953 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | YOLOv5x6 | https://arxiv.org/abs/2105.12931v3 | AP | 0.9508 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | SCRFD-34GF | https://arxiv.org/abs/2105.04714v1 | AP | 0.9492 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | + DH + HIM | http://arxiv.org/abs/1811.11662v1 | AP | 0.949 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | YOLOv5l6 | https://arxiv.org/abs/2105.12931v3 | AP | 0.949 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | SRN | http://arxiv.org/abs/1809.02693v1 | AP | 0.948 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | PyramidBox | http://arxiv.org/abs/1803.07737v2 | AP | 0.946 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | DSFD (RFB) | http://arxiv.org/abs/1810.10220v3 | AP | 0.945 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | YOLOv5s6 | https://arxiv.org/abs/2105.12931v3 | AP | 0.944 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | MogFace (HCAM) | https://arxiv.org/abs/2103.11139v5 | AP | 0.942 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | FDNet | http://arxiv.org/abs/1802.02142v1 | AP | 0.939 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | SCRFD-10GF | https://arxiv.org/abs/2105.04714v1 | AP | 0.9387 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | MogFace (Ali-AMS) | https://arxiv.org/abs/2103.11139v5 | AP | 0.936 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | WSMA-Seg | https://arxiv.org/abs/1904.13300v3 | AP | 0.9341 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | Face R-FCN | http://arxiv.org/abs/1709.05256v2 | AP | 0.931 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | YOLOv5s | https://arxiv.org/abs/2105.12931v3 | AP | 0.9261 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | S3FD(F+S+M) | http://arxiv.org/abs/1708.05237v3 | AP | 0.924 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | SCRFD-2.5GF | https://arxiv.org/abs/2105.04714v1 | AP | 0.9216 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | CenterFace | https://arxiv.org/abs/1911.03599v1 | AP | 0.921 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | Massively-large receptive fields | http://arxiv.org/abs/1612.04402v2 | AP | 0.908 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | EXTD | https://arxiv.org/abs/1906.06579v2 | AP | 0.903 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | RNNPool-Face-C | https://arxiv.org/abs/2002.11921v2 | AP | 0.89 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | img2pose | https://arxiv.org/abs/2012.07791v2 | AP | 0.890 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | SCRFD-0.5GF | https://arxiv.org/abs/2105.04714v1 | AP | 0.8812 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | CMS-RCNN | http://arxiv.org/abs/1606.05413v1 | AP | 0.874 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | LFFD | https://arxiv.org/abs/1904.10633v3 | AP | 0.865 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | Multitask Cascade CNN | http://arxiv.org/abs/1604.02878v1 | AP | 0.820 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | LDCF+ | http://arxiv.org/abs/1701.01692v1 | AP | 0.772 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | FD-CNN | https://www.researchgate.net/publication/308944615_A_Fast_Deep_Convolutional_Neural_Network_for_Face_Detection_in_Big_Visual_Data | AP | 0.740 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | Multiscale Cascade CNN | http://arxiv.org/abs/1511.06523v1 | AP | 0.636 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | Faceness-WIDER | http://arxiv.org/abs/1511.06523v1 | AP | 0.604 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | Two-stage CNN | http://arxiv.org/abs/1511.06523v1 | AP | 0.589 |
Facial Recognition and Modelling > Face Detection | WIDER Face (Medium) | ACF-WIDER | https://arxiv.org/abs/1407.4023v2 | AP | 0.588 |
Facial Recognition and Modelling > Face Detection | iCartoonFace | DASS-Detector (YOLOX XL) | https://arxiv.org/abs/2211.10641v2 | Average Precision | 90.01 |
Facial Recognition and Modelling > Face Detection | iCartoonFace | DASS-Detector (YOLOX Tiny) | https://arxiv.org/abs/2211.10641v2 | Average Precision | 87.75 |
Facial Recognition and Modelling > Face Detection | Annotated Faces in the Wild | SRN | http://arxiv.org/abs/1809.02693v1 | AP | 0.9987 |
Facial Recognition and Modelling > Face Detection | Annotated Faces in the Wild | HyperFace-ResNet | http://arxiv.org/abs/1603.01249v3 | AP | 0.9940 |
Facial Recognition and Modelling > Face Detection | Annotated Faces in the Wild | LRN + RSA | http://arxiv.org/abs/1707.09531v2 | AP | 0.9917 |
Facial Recognition and Modelling > Face Detection | Annotated Faces in the Wild | FaceBoxes | http://arxiv.org/abs/1708.05234v4 | AP | 0.9891 |
Facial Recognition and Modelling > Face Detection | Annotated Faces in the Wild | STN | http://arxiv.org/abs/1607.05477v1 | AP | 0.9835 |
Facial Recognition and Modelling > Face Detection | Annotated Faces in the Wild | DPM | https://arxiv.org/abs/1408.1656v3 | AP | 0.9721 |
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