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Three key challenges hinder the development of current deepfake video detection: (1) Temporal features can be complex and diverse: how can we identify general temporal artifacts to enhance model generalization? (2) Spatiotemporal models…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Zhiyuan Yan , Yandan Zhao , Shen Chen , Mingyi Guo , Xinghe Fu , Taiping Yao , Shouhong Ding , Li Yuan

This work explores various ways of exploring multi-task learning (MTL) techniques aimed at classifying videos as original or manipulated in cross-manipulation scenario to attend generalizability in deep fake scenario. The dataset used in…

Computer Vision and Pattern Recognition · Computer Science 2023-08-28 Pranav Balaji , Abhijit Das , Srijan Das , Antitza Dantcheva

Fake portrait video generation techniques have been posing a new threat to the society with photorealistic deep fakes for political propaganda, celebrity imitation, forged evidences, and other identity related manipulations. Following these…

Computer Vision and Pattern Recognition · Computer Science 2020-08-27 Umur Aybars Ciftci , Ilke Demir , Lijun Yin

Advances in computer vision have brought us to the point where we have the ability to synthesise realistic fake content. Such approaches are seen as a source of disinformation and mistrust, and pose serious concerns to governments around…

Computer Vision and Pattern Recognition · Computer Science 2019-11-20 Tharindu Fernando , Clinton Fookes , Simon Denman , Sridha Sridharan

The growing presence of AI-generated videos on social networks poses new challenges for deepfake detection, as detectors trained under controlled conditions often fail to generalize to real-world scenarios. A key factor behind this gap is…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Andrea Montibeller , Dasara Shullani , Daniele Baracchi , Alessandro Piva , Giulia Boato

Face-swapping techniques have advanced rapidly with the evolution of deep learning, leading to widespread use and growing concerns about potential misuse, especially in cases of fraud. While many efforts have focused on detecting swapped…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Zhongyi Zhang , Jie Zhang , Wenbo Zhou , Xinghui Zhou , Qing Guo , Weiming Zhang , Tianwei Zhang , Nenghai Yu

Although Generative Adversarial Network (GAN) can be used to generate the realistic image, improper use of these technologies brings hidden concerns. For example, GAN can be used to generate a tampered video for specific people and…

Multimedia · Computer Science 2018-10-19 Chih-Chung Hsu , Chia-Yen Lee , Yi-Xiu Zhuang

Detecting AI-generated images, particularly deepfakes, has become increasingly crucial, with the primary challenge being the generalization to previously unseen manipulation methods. This paper tackles this issue by leveraging the forgery…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Wentang Song , Zhiyuan Yan , Yuzhen Lin , Taiping Yao , Changsheng Chen , Shen Chen , Yandan Zhao , Shouhong Ding , Bin Li

Image and video forensics have recently gained increasing attention due to the proliferation of manipulated images and videos, especially on social media platforms, such as Twitter and Instagram, which spread disinformation and fake news.…

Cryptography and Security · Computer Science 2024-02-06 Maryam Al-Fehani , Saif Al-Kuwari

Conspicuous progression in the field of machine learning and deep learning have led the jump of highly realistic fake media, these media oftentimes referred as deepfakes. Deepfakes are fabricated media which are generated by sophisticated…

Machine Learning · Computer Science 2023-04-05 Aniruddha Tiwari , Rushit Dave , Mounika Vanamala

Deepfake technology has given rise to a spectrum of novel and compelling applications. Unfortunately, the widespread proliferation of high-fidelity fake videos has led to pervasive confusion and deception, shattering our faith that seeing…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Zhongjie Ba , Qingyu Liu , Zhenguang Liu , Shuang Wu , Feng Lin , Li Lu , Kui Ren

As synthetic media, including video, audio, and text, become increasingly indistinguishable from real content, the risks of misinformation, identity fraud, and social manipulation escalate. This survey traces the evolution of deepfake…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Ping Liu , Qiqi Tao , Joey Tianyi Zhou

Facial forgery methods such as deepfakes can be misused for identity manipulation and spreading misinformation. They have evolved alongside advancements in generative AI, leading to new and more sophisticated forgery techniques that diverge…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Nadarasar Bahavan , Sachith Seneviratne , Sanjay Saha , Ken Chen , Sanka Rasnayaka , Saman Halgamuge

The growing reliance of society on social media for authentic information has done nothing but increase over the past years. This has only raised the potential consequences of the spread of misinformation. One of the growing methods in…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Jacob Mallet , Natalie Krueger , Mounika Vanamala , Rushit Dave

The rapid progress in deep learning has given rise to hyper-realistic facial forgery methods, leading to concerns related to misinformation and security risks. Existing face forgery datasets have limitations in generating high-quality…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Zhongxi Chen , Ke Sun , Ziyin Zhou , Xianming Lin , Xiaoshuai Sun , Liujuan Cao , Rongrong Ji

Deepfake is a technology dedicated to creating highly realistic facial images and videos under specific conditions, which has significant application potential in fields such as entertainment, movie production, digital human creation, to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Gan Pei , Jiangning Zhang , Menghan Hu , Zhenyu Zhang , Chengjie Wang , Yunsheng Wu , Guangtao Zhai , Jian Yang , Dacheng Tao

Applications of deep learning to synthetic media generation allow the creation of convincing forgeries, called DeepFakes, with limited technical expertise. DeepFake detection is an increasingly active research area. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2021-08-31 Kevin Lutz , Robert Bassett

In the world of fake news and deepfakes, there have been an alarmingly large number of cases of images being tampered with and published in newspapers, used in court, and posted on social media for defamation purposes. Detecting these…

Computer Vision and Pattern Recognition · Computer Science 2022-02-10 Aditya Pandey , Anshuman Mitra

Face recognition from image or video is a popular topic in biometrics research. Many public places usually have surveillance cameras for video capture and these cameras have their significant value for security purpose. It is widely…

Computer Vision and Pattern Recognition · Computer Science 2013-02-27 Faizan Ahmad , Aaima Najam , Zeeshan Ahmed

With the rapid progress of recent years, techniques that generate and manipulate multimedia content can now guarantee a very advanced level of realism. The boundary between real and synthetic media has become very thin. On the one hand,…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Luisa Verdoliva
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