FaceScrub Results
Identification Rate vs. Distractors Size
| Algorithm | Date Submitted | Set 1 | Set 2 | Set 3 | Data Set Size |
|---|---|---|---|---|---|
| TencentAILab FaceCNN v1 | 08/30/2017 | 77.068% | Large | ||
| Yang Sun (Reported by Author) | 09/15/2016 | 75.786% | Large | ||
| GRCCV - GRCCV | 09/15/2016 | 75.772% | 75.772% | 75.772% | Large |
| NEC - (Kihyuk Sohn/Xiang Yu/Manmohan Chandraker) | 09/15/2016 | 62.122% | Large | ||
| Team 2009 - (GT-CMU-SYSU) | 09/15/2016 | 58.933% | Large | ||
| 3DiVi - (Andrey Bich/Andrey Tsybulevsky) | 09/15/2016 | 57.045% | Large | ||
| VeraID - (Daniel Saez Trigueros) | 09/15/2016 | 44.191% | 44.191% | 44.191% | Large |
| TSEC - (Haiyong Sun) | 09/15/2016 | 28.716% | 28.716% | 28.716% | Large |
| Baseline - Model C | 09/15/2016 | 5.357% | Large | ||
| Baseline - Model D | 09/15/2016 | 3.954% | 3.954% | 3.954% | Large |
| Baseline - Model A | 09/15/2016 | 2.13% | 2.13% | 2.13% | Large |
| Baseline - Model B | 09/15/2016 | 1.846% | Large |
Method Details
| Algorithm | Details |
|---|
Set 1
Set 1
Set 2
Set 2
Set 3
Set 3
Identification Rank vs. Rank
| Algorithm | Date Submitted | Set 1 | Set 2 | Set 3 | Data Set Size |
|---|---|---|---|---|---|
| TencentAILab FaceCNN v1 | 08/30/2017 | 77.068% | Large | ||
| Yang Sun (Reported by Author) | 09/15/2016 | 75.786% | Large | ||
| GRCCV - GRCCV | 09/15/2016 | 75.772% | 75.772% | 75.772% | Large |
| NEC - (Kihyuk Sohn/Xiang Yu/Manmohan Chandraker) | 09/15/2016 | 62.122% | Large | ||
| Team 2009 - (GT-CMU-SYSU) | 09/15/2016 | 58.933% | Large | ||
| 3DiVi - (Andrey Bich/Andrey Tsybulevsky) | 09/15/2016 | 57.045% | Large | ||
| VeraID - (Daniel Saez Trigueros) | 09/15/2016 | 44.191% | 44.191% | 44.191% | Large |
| TSEC - (Haiyong Sun) | 09/15/2016 | 28.716% | 28.716% | 28.716% | Large |
| Baseline - Model C | 09/15/2016 | 5.357% | Large | ||
| Baseline - Model D | 09/15/2016 | 3.954% | 3.954% | 3.954% | Large |
| Baseline - Model A | 09/15/2016 | 2.13% | 2.13% | 2.13% | Large |
| Baseline - Model B | 09/15/2016 | 1.846% | Large |
Method Details
| Algorithm | Details |
|---|
Identification Performance with 1 Million Distractors
Identification Performance with 10K Distractors
Set 1
Set 1
- - uses large training set
Set 2
Set 2
- - uses large training set
Set 3
Set 3
Verification
| Algorithm | Date Submitted | Set 1 | Set 2 | Set 3 | Data Set Size |
|---|---|---|---|---|---|
| TencentAILab FaceCNN v1 | 08/30/2017 | 90.302% | 90.302% | 90.302% | Large |
| Yang Sun (Reported by Author) | 09/15/2016 | 84.026% | Large | ||
| GRCCV - GRCCV | 09/15/2016 | 74.843% | 74.843% | 74.843% | Large |
| Team 2009 - (GT-CMU-SYSU) | 09/15/2016 | 71.124% | 71.124% | 71.124% | Large |
| NEC - (Kihyuk Sohn/Xiang Yu/Manmohan Chandraker) | 09/15/2016 | 66.845% | 66.845% | 66.845% | Large |
| 3DiVi - (Andrey Bich/Andrey Tsybulevsky) | 09/15/2016 | 66.458% | 66.458% | 66.458% | Large |
| VeraID - (Daniel Saez Trigueros) | 09/15/2016 | 48.087% | 48.087% | 48.087% | Large |
| TSEC - (Haiyong Sun) | 09/15/2016 | 7.478% | 7.478% | 7.478% | Large |
| Baseline - Model D | 09/15/2016 | 3.01% | 3.01% | 3.01% | Large |
| Baseline - Model C | 09/15/2016 | 1.655% | 1.655% | 1.655% | Large |
| Baseline - Model B | 09/15/2016 | 1.351% | 1.351% | 1.351% | Large |
| Baseline - Model A | 09/15/2016 | 1.328% | 1.328% | 1.328% | Large |
Method Details
| Algorithm | Details |
|---|
Verification Performance with 1 Million Distractors
Verifification Performance with 10K Distractors
Set 1
Set 1
Set 2
Set 2
Set 3
Set 3
