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 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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