Deep Detection for Face Manipulation

09/13/2020
by   Disheng Feng, et al.
0

It has become increasingly challenging to distinguish real faces from their visually realistic fake counterparts, due to the great advances of deep learning based face manipulation techniques in recent years. In this paper, we introduce a deep learning method to detect face manipulation. It consists of two stages: feature extraction and binary classification. To better distinguish fake faces from real faces, we resort to the triplet loss function in the first stage. We then design a simple linear classification network to bridge the learned contrastive features with the real/fake faces. Experimental results on public benchmark datasets demonstrate the effectiveness of this method, and show that it generates better performance than state-of-the-art techniques in most cases.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/12/2021

Challenges and Solutions in DeepFakes

Deep learning has been successfully appertained to solve various complex...
research
11/17/2019

Exploiting Human Social Cognition for the Detection of Fake and Fraudulent Faces via Memory Networks

Advances in computer vision have brought us to the point where we have t...
research
10/27/2020

Mining Generalized Features for Detecting AI-Manipulated Fake Faces

Recently, AI-manipulated face techniques have developed rapidly and cons...
research
07/13/2021

Detect and Locate: A Face Anti-Manipulation Approach with Semantic and Noise-level Supervision

The technological advancements of deep learning have enabled sophisticat...
research
10/11/2022

Aggregating Layers for Deepfake Detection

The increasing popularity of facial manipulation (Deepfakes) and synthet...
research
03/15/2023

Real Face Foundation Representation Learning for Generalized Deepfake Detection

The emergence of deepfake technologies has become a matter of social con...
research
10/31/2018

Face Presentation Attack Detection in Learned Color-liked Space

Face presentation attack detection (PAD) has become a thorny problem for...

Please sign up or login with your details

Forgot password? Click here to reset