task_path
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⌀ | dataset
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⌀ | model_name
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⌀ | metric_value
stringlengths 1
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⌀ |
|---|---|---|---|---|---|
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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