Deep Frequent Spatial Temporal Learning for Face Anti-Spoofing

Understand

Face anti-spoofing is crucial for the security of face recognition system, by avoiding invaded with presentation attack.

• Previous works have shown the effectiveness of using depth and temporal supervision for this task.
• However, depth supervision is often considered only in a single frame, and temporal supervision is explored by utilizing certain signals which is not robust to the change of scenes.
• In this work, motivated by two stream ConvNets, we propose a novel two stream FreqSaptialTemporalNet for face anti-spoofing which simultaneously takes advantage of frequent, spatial and temporal information.