PADify (pronounced as /ˈpædfaɪ/) is a project to perform presentation attack detection (PAD) on publicly available datasets by using different intrinsic image properties along with Convolutional Neural Networks.
Fig 1 - Examples of Presentation Attack Detection
Fig 2 - Overview of proposed method
- Illuminant Maps (Carvalho et al.)
- Saliency (Zhu et al.)
- Depth (Godard et al.)
- CASIA Face Anti-Spoofing Database
- Replay Attack
- NUAA Imposter Database
- ROSE-Youtu Face Liveness Detection Dataset (In Progress)
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