Detection of Spoofing Medium Contours for Face Anti-Spoofing

Face anti-spoofing is an important step for secure face recognition. In this paper, we target on building a general classifier to detect the face images with spoofing medium contours (termed as SMCs for simplicity). To this end, we consider the task of face anti-spoofing as the detection of SMCs from the image. We propose and train a Contour Enhanced Mask R-CNN (CEM-RCNN) model for the detection. This model detects the existence of the SMCs by incorporating the contour objectness which measures how likely an object contains the SMCs. The experimental results demonstrate the generality of the CEM-RCNN for identifying the face images with SMCs, which performs significantly better than the state-of-the-art on the cross-database scenario.

Automated summary

This paper proposes a Contour Enhanced Mask R-CNN (CEM-RCNN) model for detecting face images with spoofing medium contours (SMCs), and experimental results demonstrate its significantly better performance than the state-of-the-art technology in cross-database scenarios.