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⌀ | dataset
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⌀ | model_name
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⌀ | metric_name
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⌀ | metric_value
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9.22k
⌀ |
|---|---|---|---|---|---|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
3.65
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
306.11
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.9693
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
Seesaw-shuffleFaceNet(mobi)
|
https://arxiv.org/abs/1908.09124v3
|
MParams
|
2.8
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
Seesaw-shuffleFaceNet(mobi)
|
https://arxiv.org/abs/1908.09124v3
|
Accuracy
|
0.9648
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
PocketNetS
|
https://arxiv.org/abs/2108.10710v2
|
Accuracy
|
0.9635
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
1.77
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
154
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.96
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
AgeDB-30
|
MobileFaceNet
|
http://arxiv.org/abs/1804.07573v4
|
Accuracy
|
0.9305
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CFP-FP
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.9581
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CFP-FP
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
306.11
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CFP-FP
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
3.65
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CFP-FP
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.9437
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CFP-FP
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
154
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CFP-FP
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
1.77
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CFP-FP
|
PocketNetS
|
https://arxiv.org/abs/2108.10710v2
|
Accuracy
|
0.9334
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CFP-FP
|
Seesaw-shuffleFaceNet(mobi)
|
https://arxiv.org/abs/1908.09124v3
|
Accuracy
|
0.9307
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CFP-FP
|
Seesaw-shuffleFaceNet(mobi)
|
https://arxiv.org/abs/1908.09124v3
|
MParams
|
2.8
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.9978
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
306.11
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
3.65
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.9973
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
154
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
1.77
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
PocketNetS
|
https://arxiv.org/abs/2108.10710v2
|
Accuracy
|
0.9966
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
PocketNetS
|
https://arxiv.org/abs/2108.10710v2
|
MFLOPs
|
587.24
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
PocketNetS
|
https://arxiv.org/abs/2108.10710v2
|
MParams
|
0.99
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
Seesaw-shuffleFaceNet(mobi)
|
https://arxiv.org/abs/1908.09124v3
|
Accuracy
|
0.9965
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
Seesaw-shuffleFaceNet(mobi)
|
https://arxiv.org/abs/1908.09124v3
|
MParams
|
2.8
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
MixFaceNet-S
|
https://arxiv.org/abs/2107.13046v1
|
Accuracy
|
0.996
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
MixFaceNet-S
|
https://arxiv.org/abs/2107.13046v1
|
MFLOPs
|
451.7
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
MixFaceNet-S
|
https://arxiv.org/abs/2107.13046v1
|
MParams
|
3.07
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
LFW
|
MobileFaceNet
|
http://arxiv.org/abs/1804.07573v4
|
Accuracy
|
0.9928
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CALFW
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.9571
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CALFW
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
306.11
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CALFW
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
3.65
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CALFW
|
PocketNetS
|
https://arxiv.org/abs/2108.10710v2
|
Accuracy
|
0.955
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CALFW
|
PocketNetS
|
https://arxiv.org/abs/2108.10710v2
|
MParams
|
0.99
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CALFW
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.9528
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CALFW
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
154
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CALFW
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
1.77
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CPLFW
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.9256
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CPLFW
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
306.11
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CPLFW
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
3.65
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CPLFW
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
Accuracy
|
0.9182
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CPLFW
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
154
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CPLFW
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
1.77
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
CPLFW
|
PocketNetS
|
https://arxiv.org/abs/2108.10710v2
|
Accuracy
|
0.8893
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-C
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
TAR @ FAR=0.01
|
0.9563
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-C
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
306.11
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-C
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
3.65
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-C
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
TAR @ FAR=0.01
|
0.9485
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-C
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
154
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-C
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
1.77
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-C
|
MixFaceNet-S
|
https://arxiv.org/abs/2107.13046v1
|
TAR @ FAR=0.01
|
0.9230
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-C
|
MixFaceNet-S
|
https://arxiv.org/abs/2107.13046v1
|
MFLOPs
|
451.7
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-B
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
TAR @ FAR=0.01
|
0.9358
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-B
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
306.11
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-B
|
EdgeFace - S (g=0.5)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
3.65
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-B
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
TAR @ FAR=0.01
|
0.9267
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-B
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MFLOPs
|
154
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-B
|
EdgeFace - XS (g=0.6)
|
https://arxiv.org/abs/2307.01838v2
|
MParams
|
1.77
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-B
|
MixFaceNet-S
|
https://arxiv.org/abs/2107.13046v1
|
TAR @ FAR=0.01
|
0.9017
|
Facial Recognition and Modelling > Face Recognition > Lightweight Face Recognition
|
IJB-B
|
MixFaceNet-S
|
https://arxiv.org/abs/2107.13046v1
|
MFLOPs
|
451.7
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
CPLFW
|
SynthDistill
|
https://arxiv.org/abs/2308.14852v1
|
Accuracy
|
0.8700
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
CPLFW
|
DigiFace-1M
|
https://arxiv.org/abs/2210.02579v1
|
Accuracy
|
0.8223
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
CPLFW
|
IDiff-Face
|
https://arxiv.org/abs/2308.04995v2
|
Accuracy
|
0.8045
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
LFW
|
SynthDistill
|
https://arxiv.org/abs/2308.14852v1
|
Accuracy
|
0.9952
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
LFW
|
IDiff-Face
|
https://arxiv.org/abs/2308.04995v2
|
Accuracy
|
0.98
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
LFW
|
DigiFace-1M
|
https://arxiv.org/abs/2210.02579v1
|
Accuracy
|
0.9617
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
CALFW
|
SynthDistill
|
https://arxiv.org/abs/2308.14852v1
|
Accuracy
|
0.9457
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
CALFW
|
IDiff-Face
|
https://arxiv.org/abs/2308.04995v2
|
Accuracy
|
0.9065
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
CALFW
|
DigiFace-1M
|
https://arxiv.org/abs/2210.02579v1
|
Accuracy
|
0.8255
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
AgeDB-30
|
SynthDistill
|
https://arxiv.org/abs/2308.14852v1
|
Accuracy
|
0.9493
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
AgeDB-30
|
IDiff-Face
|
https://arxiv.org/abs/2308.04995v2
|
Accuracy
|
0.8643
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
AgeDB-30
|
DigiFace-1M
|
https://arxiv.org/abs/2210.02579v1
|
Accuracy
|
0.811
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
CFP-FP
|
SynthDistill
|
https://arxiv.org/abs/2308.14852v1
|
Accuracy
|
0.9089
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
CFP-FP
|
DigiFace-1M
|
https://arxiv.org/abs/2210.02579v1
|
Accuracy
|
0.8981
|
Facial Recognition and Modelling > Face Recognition > Synthetic Face Recognition
|
CFP-FP
|
IDiff-Face
|
https://arxiv.org/abs/2308.04995v2
|
Accuracy
|
0.8547
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
FG-NET
|
MTLFace
|
https://arxiv.org/abs/2103.01520v2
|
Accuracy
|
94.78%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
FG-NET
|
AIM
|
http://arxiv.org/abs/1809.00338v2
|
Accuracy
|
93.2%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CAFR
|
AIM
|
http://arxiv.org/abs/1809.00338v2
|
Accuracy
|
84.81%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CAFR
|
Light CNN
|
http://arxiv.org/abs/1511.02683v4
|
Accuracy
|
73.56%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CACDVS
|
AIM + CAFR
|
http://arxiv.org/abs/1809.00338v2
|
Accuracy
|
99.76%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CACDVS
|
MTLFace
|
https://arxiv.org/abs/2103.01520v2
|
Accuracy
|
99.55%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CACDVS
|
DAL
|
http://arxiv.org/abs/1904.04972v1
|
Accuracy
|
99.4%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CACDVS
|
AIM
|
http://arxiv.org/abs/1809.00338v2
|
Accuracy
|
99.38%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CACDVS
|
OE-CNN
|
http://arxiv.org/abs/1810.07599v1
|
Accuracy
|
99.2%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CACDVS
|
DeepVisage
|
http://arxiv.org/abs/1703.08388v2
|
Accuracy
|
99.13%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CACDVS
|
LF-CNNs
|
http://openaccess.thecvf.com/content_cvpr_2016/html/Wen_Latent_Factor_Guided_CVPR_2016_paper.html
|
Accuracy
|
98.5
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CACDVS
|
MFM-CNN
|
http://arxiv.org/abs/1511.02683v4
|
Accuracy
|
97.95%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
CACDVS
|
High-Dimensional LBP
|
http://openaccess.thecvf.com/content_cvpr_2013/html/Chen_Blessing_of_Dimensionality_2013_CVPR_paper.html
|
Accuracy
|
81.6
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
MORPH Album2
|
AIM + CAFR
|
http://arxiv.org/abs/1809.00338v2
|
Rank-1 Recognition Rate
|
99.65%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
MORPH Album2
|
AIM
|
http://arxiv.org/abs/1809.00338v2
|
Rank-1 Recognition Rate
|
99.13%
|
Facial Recognition and Modelling > Face Recognition > Age-Invariant Face Recognition
|
MORPH Album2
|
OE-CNN
|
http://arxiv.org/abs/1810.07599v1
|
Rank-1 Recognition Rate
|
98.55%
|
Facial Recognition and Modelling > Face Recognition > Face Quality Assessement
|
LFW
|
SER-FIQ (same model) on ArcFace
|
https://arxiv.org/abs/2003.09373v1
|
Equal Error Rate
|
0.007
|
Facial Recognition and Modelling > Face Recognition > Face Quality Assessement
|
mebeblurf
|
SER-FIQ (same model) on FaceNet
|
https://arxiv.org/abs/2003.09373v1
|
Equal Error Rate
|
0.026
|
Facial Recognition and Modelling > Face Recognition > Face Quality Assessement
|
Color FERET
|
monet
|
https://arxiv.org/abs/2207.09505v1
|
Pearson Correlation
|
0.686
|
Facial Recognition and Modelling > Face Recognition > Unsupervised face recognition
|
LFW
|
USynthFace
|
https://arxiv.org/abs/2211.07371v1
|
Accuracy (%)
|
92.23
|
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