Face image manipulation detection based on a convolutional neural network

作者：

Highlights：

• Proposing MANFA – a customized CNN model for manipulated face detection.

• Integrating XGBoost, and AdaBoost with MANFA to cope with the extreme imbalanced dataset.

• Proposing a manually collected dataset (8950 images) for altered face detection.

摘要

•Proposing MANFA – a customized CNN model for manipulated face detection.•Integrating XGBoost, and AdaBoost with MANFA to cope with the extreme imbalanced dataset.•Proposing a manually collected dataset (8950 images) for altered face detection.

论文关键词：Image manipulation,Deep learning,AdaBoost,XGBoost,Imbalanced dataset,Boosting

论文评审过程：Received 13 August 2018, Revised 4 April 2019, Accepted 4 April 2019, Available online 5 April 2019, Version of Record 10 April 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.04.005