Facial Retouching and Alteration Detection

Author:

Majumdar Puspita,Agarwal Akshay,Vatsa Mayank,Singh Richa

Abstract

AbstractOn the social media platforms, thefiltersfor digital retouching and face beautification have become a common trend. With the availability of easy-to-use image editing tools, the generation of altered images has become an effortless task. Apart from this, advancements in the Generative Adversarial Network (GAN) leads to creation of realistic facial images and alteration of facial images based on the attributes. While the majority of these images are created for fun and beautification purposes, they may be used with malicious intent for negative applications such as deepnude or spreading visual fake news. Therefore, it is important to detect digital alterations in images and videos. This chapter presents a comprehensive survey of existing algorithms for retouched and altered image detection. Further, multiple experiments are performed to highlight the open challenges of alteration detection.

Publisher

Springer International Publishing

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Subjective and Objective Quality Assessment of Multi-Attribute Retouched Face Images;IEEE Transactions on Broadcasting;2024-06

2. Motion Magnified 3-D Residual-in-Dense Network for DeepFake Detection;IEEE Transactions on Biometrics, Behavior, and Identity Science;2023-01

3. Mannet: A Large-Scale Manipulated Image Detection Dataset And Baseline Evaluations;ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2022-05-23

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