Manipulated Faces Detection with Adaptive Filter

Abstract

With the progress of face manipulation techniques, synthesized faces are spreading on the Internet, which raises concerns about potential threats. To prevent these techniques’ abuse, various detection algorithms have been proposed. In this paper, we consider the image’s frequency information, then propose an adaptive filtering algorithm named spatial and adaptive filtering (SAF) Network. SAF is a dual-stream network that considers spatial and frequency domains. In the frequency domain, wavelet transform is used to divide the image into different frequency bands, then an adaptive filter is introduced, which aims to capture more decisive information by giving different weights to different frequencies. To fuse spatial and frequency features, spatial pyramid pooling fusion (SPPF) is proposed, which solves the mismatch of feature maps, and considers the relationship between different patches by attention mechanism. Experiment results show that the performance of SAF is better than the comparison algorithm.