Face Recognition Models
Negative Face Recognition
Introduced by Terhörst et al. in Unsupervised Enhancement of Soft-biometric Privacy with Negative Face RecognitionNegative Face Recognition, or NFR, is a face recognition approach that enhances the soft-biometric privacy on the template-level by representing face templates in a complementary (negative) domain. While ordinary templates characterize facial properties of an individual, negative templates describe facial properties that does not exist for this individual. This suppresses privacy-sensitive information from stored templates. Experiments are conducted on two publicly available datasets captured under controlled and uncontrolled scenarios on three privacy-sensitive attributes.
Source: Unsupervised Enhancement of Soft-biometric Privacy with Negative Face Recognition
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Classification | 1 | 12.50% |
| Zero-Shot Learning | 1 | 12.50% |
| 3D Reconstruction | 1 | 12.50% |
| Machine Translation | 1 | 12.50% |
| NMT | 1 | 12.50% |
| Sentence | 1 | 12.50% |
| Translation | 1 | 12.50% |
| Face Recognition | 1 | 12.50% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
