Results 11 to 20 of about 2,792,706 (240)

A Survey on Photo Forgery Detection Methods

ITM Web of Conferences, 2018
In recent years, digital image forgery detection has become one of the hardest studying area for researchers investigations in the field of information security and image processing.
Gurunlu Bilgehan, Ozturk Serkan
doaj   +2 more sources

Spatiotemporal Consistency-Based Deep Forgery Detection [PDF]

ITM Web of Conferences
With the rapid development of generative artificial intelligence (AIGC) and deep learning technology, deep forgery technology based on generated adversarial network (GAN) and diffusion model can generate extremely realistic facial videos and images ...
Wen Peng
doaj   +2 more sources

CoMoFoD #x2014; New database for copy-move forgery detection [PDF]

, 2013
Due to the availability of many sophisticated image processing tools, a digital image forgery is nowadays very often used. One of the common forgery method is a copy-move forgery, where part of an image is copied to another location in the same image ...
Grgic, M, Zupancic, I, Tralic, D, Grgic, S   +3 more
core   +4 more sources

Facial depth forgery detection based on image gradient

, 2023
With the widespread application of deep learning, many artificially generated fake images and videos appear on the Internet. However, it is difficult for people to distinguish the real from the fake ones, making the research on detecting and recognizing ...
Fang, Xianjin, Yang, Gaoming, Xu, Kun, Zhang, Ji, Kun Xu, Gaoming Yang, Xianjin Fang, Ji Zhang   +7 more
core   +1 more source

Video face forgery detection via facial motion-assisted capturing dense optical flow truncation

, 2023
Deep learning advancements have resulted in breakthroughs in facial forgery techniques. Facial forgery videos are growing increasingly lifelike, making it impossible for people to tell the difference between the real and the fake.
Fang, Xianjin, Yang, Gaoming, Xu, Kun, Zhang, Ji   +3 more
core   +1 more source

Face Forgery Detection and Attribution via Prototype Disentanglement [PDF]

Jisuanji kexue yu tansuo
The detection and attribution of face forgery aims to determine whether a face in an image or video has been manipulated or synthesized using Deepfake techniques, as well as to further analyze the Deepfake method behind it.
QIAN Fei, LI Wei, CHEN Peng, CHEN Haoran, XIE Lipeng, LIU Liyuan
doaj   +1 more source

Multi-Feature Fusion Based Deepfake Face Forgery Video Detection

Systems, 2022
With the rapid development of deep learning, generating realistic fake face videos is becoming easier. It is common to make fake news, network pornography, extortion and other related illegal events using deep forgery.
Zhimao Lai, Yufei Wang, Renhai Feng, Xianglei Hu, Haifeng Xu   +4 more
doaj   +1 more source

Image forgery detection review

, 2021
With the wide spread of digital document use in administrations, fabrication and use of forged documents have become a serious problem. This paper presents a study and classification of the most important works on image and document forgery detection ...
Benhamza, Hiba,, Hiba Benhamza, Abbas Cheddad, Cheddad, Abbas, Cheddad, Abbas,, Abdelhamid Djeffal, Benhamza, Hiba, Djeffal, Abdelhamid, Djeffal, Abdelhamid,   +8 more
core   +1 more source

Seamless Copy–Move Replication in Digital Images

Journal of Imaging, 2022
The importance and relevance of digital-image forensics has attracted researchers to establish different techniques for creating and detecting forgeries.
Tanzeela Qazi, Mushtaq Ali, Khizar Hayat, Baptiste Magnier   +3 more
doaj   +1 more source

ENF Based Video Forgery Detection Algorithm

, 2020
The electric network frequency (ENF) is recorded in the videos taken under the lights powered by grid and can be used for digital forensics. However, due to the lack of data caused by the low frame rate of the video, the ENF-based forensics methods ...
Yufei Wang, Alan Liew, Wang, Y, Hu, Y, Liew, AWC, Yongjian Hu, Chang-Tsun Li, Li, CT   +7 more
core   +1 more source