Using Fully Convolutional Neural Networks to detect manipulated images in videos

11/29/2019
by   Michail Tarasiou, et al.
1

We propose a compact architecture based on fully convolutional neural networks (FCN) to detect manipulated images of human faces. In contrast to existing FCN architectures for classification, here the final layer feature map exhibits large spatial dimensions with non-global receptive field. The final layer features are spatially averaged using global average pooling (GAP) to provide more robust features. We leverage the structure of the FCN to derive a straightforward way for joint classification and forgery localization training and show that the network's classification performance improves significantly by the addition of a pixelwise classification loss. The trained networks achieve state of the art results in binary classification in the FaceForensics++ dataset and competitive performance in other tasks using a significantly reduced number of parameters and small resolution input images. Additionally, we examine how well the proposed architecture can detect fully generated images using faces from the recently proposed PGAN and StyleGAN methods. We show that this task is easier to learn than detecting manipulated images and that for both cases there is only a small drop of performance when the network is trained using more than one manipulation technique in the training data.

READ FULL TEXT

page 3

page 5

page 7

research
09/20/2019

Persian Signature Verification using Fully Convolutional Networks

Fully convolutional networks (FCNs) have been recently used for feature ...
research
08/10/2017

Document Image Binarization with Fully Convolutional Neural Networks

Binarization of degraded historical manuscript images is an important pr...
research
05/05/2019

Embedding Structured Contour and Location Prior in Siamesed Fully Convolutional Networks for Road Detection

Road detection from the perspective of moving vehicles is a challenging ...
research
01/07/2022

Multiresolution Fully Convolutional Networks to detect Clouds and Snow through Optical Satellite Images

Clouds and snow have similar spectral features in the visible and near-i...
research
09/03/2016

Deep-Anomaly: Fully Convolutional Neural Network for Fast Anomaly Detection in Crowded Scenes

The detection of abnormal behaviours in crowded scenes has to deal with ...
research
07/07/2012

Object Recognition with Multi-Scale Pyramidal Pooling Networks

We present a Multi-Scale Pyramidal Pooling Network, featuring a novel py...
research
06/18/2018

Detecting and interpreting myocardial infarctions using fully convolutional neural networks

We consider the detection of myocardial infarction in electrocardiograph...

Please sign up or login with your details

Forgot password? Click here to reset