Collaborative Feature Learning for Fine-grained Facial Forgery Detection and Segmentation

by   Weinan Guan, et al.

Detecting maliciously falsified facial images and videos has attracted extensive attention from digital-forensics and computer-vision communities. An important topic in manipulation detection is the localization of the fake regions. Previous work related to forgery detection mostly focuses on the entire faces. However, recent forgery methods have developed to edit important facial components while maintaining others unchanged. This drives us to not only focus on the forgery detection but also fine-grained falsified region segmentation. In this paper, we propose a collaborative feature learning approach to simultaneously detect manipulation and segment the falsified components. With the collaborative manner, detection and segmentation can boost each other efficiently. To enable our study of forgery detection and segmentation, we build a facial forgery dataset consisting of both entire and partial face forgeries with their pixel-level manipulation ground-truth. Experiment results have justified the mutual promotion between forgery detection and manipulated region segmentation. The overall performance of the proposed approach is better than the state-of-the-art detection or segmentation approaches. The visualization results have shown that our proposed model always captures the artifacts on facial regions, which is more reasonable.


page 1

page 3

page 5

page 6


On the Detection of Digital Face Manipulation

Detecting manipulated facial images and videos is an increasingly import...

Towards Generalizable Forgery Detection with Locality-aware AutoEncoder

With advancements of deep learning techniques, it is now possible to gen...

A Machine Learning Approach for DeepFake Detection

With the spread of DeepFake techniques, this technology has become quite...

FFR_FD: Effective and Fast Detection of DeepFakes Based on Feature Point Defects

The internet is filled with fake face images and videos synthesized by d...

Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localization

The rapid advancements in computer vision have stimulated remarkable pro...

Robust Face-Swap Detection Based on 3D Facial Shape Information

Maliciously-manipulated images or videos - so-called deep fakes - especi...

Please sign up or login with your details

Forgot password? Click here to reset