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As neural networks become able to generate realistic artificial images, they have the potential to improve movies, music, video games and make the internet an even more creative and inspiring place. Yet, the latest technology potentially…

Computer Vision and Pattern Recognition · Computer Science 2022-09-02 Moritz Wolter , Felix Blanke , Raoul Heese , Jochen Garcke

This paper presents a method to automatically and efficiently detect face tampering in videos, and particularly focuses on two recent techniques used to generate hyper-realistic forged videos: Deepfake and Face2Face. Traditional image…

Computer Vision and Pattern Recognition · Computer Science 2021-04-27 Darius Afchar , Vincent Nozick , Junichi Yamagishi , Isao Echizen

The fast and continuous growth in number and quality of deepfake videos calls for the development of reliable detection systems capable of automatically warning users on social media and on the Internet about the potential untruthfulness of…

Computer Vision and Pattern Recognition · Computer Science 2020-11-17 Luca Bondi , Edoardo Daniele Cannas , Paolo Bestagini , Stefano Tubaro

We propose a method for detecting face swapping and other identity manipulations in single images. Face swapping methods, such as DeepFake, manipulate the face region, aiming to adjust the face to the appearance of its context, while…

Computer Vision and Pattern Recognition · Computer Science 2020-08-28 Yuval Nirkin , Lior Wolf , Yosi Keller , Tal Hassner

Following the recent initiatives for the democratization of AI, deep fake generators have become increasingly popular and accessible, causing dystopian scenarios towards social erosion of trust. A particular domain, such as biological…

Computer Vision and Pattern Recognition · Computer Science 2021-05-21 Ilke Demir , Umur A. Ciftci

With rapid advancements in generative modeling, deepfake techniques are increasingly narrowing the gap between real and synthetic videos, raising serious privacy and security concerns. Beyond traditional face swapping and reenactment, an…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Tharun Anand , Siva Sankar Sajeev , Pravin Nair

Better generative models and larger datasets have led to more realistic fake videos that can fool the human eye but produce temporal and spatial artifacts that deep learning approaches can detect. Most current Deepfake detection methods…

Computer Vision and Pattern Recognition · Computer Science 2020-06-29 Oscar de Lima , Sean Franklin , Shreshtha Basu , Blake Karwoski , Annet George

The recent computer graphics developments have upraised the quality of the generated digital content, astonishing the most skeptical viewer. Games and movies have taken advantage of this fact but, at the same time, these advances have…

Computer Vision and Pattern Recognition · Computer Science 2017-11-29 Edmar R. S. de Rezende , Guilherme C. S. Ruppert , Antonio Theophilo , Tiago Carvalho

Face-swap DeepFake is an emerging AI-based face forgery technique that can replace the original face in a video with a generated face of the target identity while retaining consistent facial attributes such as expression and orientation.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Pu Sun , Honggang Qi , Yuezun Li , Siwei Lyu

Deepfake technology is widely used, which has led to serious worries about the authenticity of digital media, making the need for trustworthy deepfake face recognition techniques more urgent than ever. This study employs a…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Faysal Mahmud , Yusha Abdullah , Minhajul Islam , Tahsin Aziz

With the recent advancements in generative modeling, the realism of deepfake content has been increasing at a steady pace, even reaching the point where people often fail to detect manipulated media content online, thus being deceived into…

We present a novel approach for the detection of deepfake videos using a pair of vision transformers pre-trained by a self-supervised masked autoencoding setup. Our method consists of two distinct components, one of which focuses on…

Computer Vision and Pattern Recognition · Computer Science 2024-02-12 Sayantan Das , Mojtaba Kolahdouzi , Levent Özparlak , Will Hickie , Ali Etemad

Detecting deepfake videos is highly challenging given the complexity of characterizing spatio-temporal artifacts. Most existing methods rely on binary classifiers trained using real and fake image sequences, therefore hindering their…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Dat Nguyen , Marcella Astrid , Anis Kacem , Enjie Ghorbel , Djamila Aouada

Deep Learning has been successfully applied in diverse fields, and its impact on deepfake detection is no exception. Deepfakes are fake yet realistic synthetic content that can be used deceitfully for political impersonation, phishing,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Ammarah Hashmi , Sahibzada Adil Shahzad , Chia-Wen Lin , Yu Tsao , Hsin-Min Wang

Deepfakes is a branch of malicious techniques that transplant a target face to the original one in videos, resulting in serious problems such as infringement of copyright, confusion of information, or even public panic. Previous efforts for…

Computer Vision and Pattern Recognition · Computer Science 2021-04-12 Zekun Sun , Yujie Han , Zeyu Hua , Na Ruan , Weijia Jia

The development of technologies for easily and automatically falsifying video has raised practical questions about people's ability to detect false information online. How vulnerable are people to deepfake videos? What technologies can be…

Human-Computer Interaction · Computer Science 2023-04-11 Emilie Josephs , Camilo Fosco , Aude Oliva

The rapid advancement of video generation models has enabled the creation of highly realistic synthetic media, raising significant societal concerns regarding the spread of misinformation. However, current detection methods suffer from…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Zhengcen Li , Chenyang Jiang , Hang Zhao , Shiyang Zhou , Yunyang Mo , Feng Gao , Fan Yang , Qiben Shan , Shaocong Wu , Jingyong Su

Video forgery detection is becoming an important issue in recent years, because modern editing software provide powerful and easy-to-use tools to manipulate videos. In this paper we propose to perform detection by means of deep learning,…

Computer Vision and Pattern Recognition · Computer Science 2017-08-30 Dario D'Avino , Davide Cozzolino , Giovanni Poggi , Luisa Verdoliva

Deepfake videos are causing growing concerns among communities due to their ever-increasing realism. Naturally, automated detection of forged Deepfake videos is attracting a proportional amount of interest of researchers. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Yunzhuo Chen , Naveed Akhtar , Nur Al Hasan Haldar , Ajmal Mian

The emergence of contemporary deepfakes has attracted significant attention in machine learning research, as artificial intelligence (AI) generated synthetic media increases the incidence of misinterpretation and is difficult to distinguish…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Ammarah Hashmi , Sahibzada Adil Shahzad , Chia-Wen Lin , Yu Tsao , Hsin-Min Wang
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