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Related papers: DFGC 2021: A DeepFake Game Competition

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This paper presents the summary report on our DFGC 2022 competition. The DeepFake is rapidly evolving, and realistic face-swaps are becoming more deceptive and difficult to detect. On the contrary, methods for detecting DeepFakes are also…

Computer Vision and Pattern Recognition · Computer Science 2022-10-05 Bo Peng , Wei Xiang , Yue Jiang , Wei Wang , Jing Dong , Zhenan Sun , Zhen Lei , Siwei Lyu

Deepfakes are a recent off-the-shelf manipulation technique that allows anyone to swap two identities in a single video. In addition to Deepfakes, a variety of GAN-based face swapping methods have also been published with accompanying code.…

Computer Vision and Pattern Recognition · Computer Science 2020-10-29 Brian Dolhansky , Joanna Bitton , Ben Pflaum , Jikuo Lu , Russ Howes , Menglin Wang , Cristian Canton Ferrer

The rapid advancement of deepfake technology has significantly elevated the realism and accessibility of synthetic media. Emerging techniques, such as diffusion-based models and Neural Radiance Fields (NeRF), alongside enhancements in…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Md. Tarek Hasan , Sanjay Saha , Shaojing Fan , Swakkhar Shatabda , Terence Sim

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

With the rapid development of technology in the field of AI, deepfake technology has emerged as a double-edged sword. It has not only created a large amount of AI-generated content but also posed unprecedented challenges to digital…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Xiaoya Zhu , Yibing Nan , Shiguo Lian

Generative deep learning algorithms have progressed to a point where it is difficult to tell the difference between what is real and what is fake. In 2018, it was discovered how easy it is to use this technology for unethical and malicious…

Computer Vision and Pattern Recognition · Computer Science 2020-09-23 Yisroel Mirsky , Wenke Lee

Deepfakes, particularly those involving faceswap-based manipulations, have sparked significant societal concern due to their increasing realism and potential for misuse. Despite rapid advancements in generative models, detection methods…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Simiao Ren , Hengwei Xu , Tsang Ng , Kidus Zewde , Shengkai Jiang , Ramini Desai , Disha Patil , Ning-Yau Cheng , Yining Zhou , Ragavi Muthukrishnan

The rapid advancement in deep learning makes the differentiation of authentic and manipulated facial images and video clips unprecedentedly harder. The underlying technology of manipulating facial appearances through deep generative…

Computer Vision and Pattern Recognition · Computer Science 2021-09-08 Sm Zobaed , Md Fazle Rabby , Md Istiaq Hossain , Ekram Hossain , Sazib Hasan , Asif Karim , Khan Md. Hasib

Currently, the rapid development of computer vision and deep learning has enabled the creation or manipulation of high-fidelity facial images and videos via deep generative approaches. This technology, also known as deepfake, has achieved…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Lixia Ma , Puning Yang , Yuting Xu , Ziming Yang , Peipei Li , Huaibo Huang

The free access to large-scale public databases, together with the fast progress of deep learning techniques, in particular Generative Adversarial Networks, have led to the generation of very realistic fake content with its corresponding…

Computer Vision and Pattern Recognition · Computer Science 2020-06-22 Ruben Tolosana , Ruben Vera-Rodriguez , Julian Fierrez , Aythami Morales , Javier Ortega-Garcia

In this paper, we present the Global Multimedia Deepfake Detection held concurrently with the Inclusion 2024. Our Multimedia Deepfake Detection aims to detect automatic image and audio-video manipulations including but not limited to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Yi Zhang , Weize Gao , Changtao Miao , Man Luo , Jianshu Li , Wenzhong Deng , Zhe Li , Bingyu Hu , Weibin Yao , Yunfeng Diao , Wenbo Zhou , Tao Gong , Qi Chu

DeepFake technology has gained significant attention due to its ability to manipulate facial attributes with high realism, raising serious societal concerns. Face-Swap DeepFake is the most harmful among these techniques, which fabricates…

Computer Vision and Pattern Recognition · Computer Science 2024-10-17 Pu Sun , Honggang Qi , Yuezun Li

Facially manipulated images and videos or DeepFakes can be used maliciously to fuel misinformation or defame individuals. Therefore, detecting DeepFakes is crucial to increase the credibility of social media platforms and other media…

Computer Vision and Pattern Recognition · Computer Science 2020-11-20 Paarth Neekhara , Brian Dolhansky , Joanna Bitton , Cristian Canton Ferrer

Due to the rising threat of deepfakes to security and privacy, it is most important to develop robust and reliable detectors. In this paper, we examine the need for high-quality samples in the training datasets of such detectors.…

Computer Vision and Pattern Recognition · Computer Science 2023-05-17 Arian Beckmann , Anna Hilsmann , Peter Eisert

The creation or manipulation of facial appearance through deep generative approaches, known as DeepFake, have achieved significant progress and promoted a wide range of benign and malicious applications, e.g., visual effect assistance in…

Computer Vision and Pattern Recognition · Computer Science 2022-03-24 Felix Juefei-Xu , Run Wang , Yihao Huang , Qing Guo , Lei Ma , Yang Liu

The rapid advancement of AI technologies has significantly increased the diversity of DeepFake videos circulating online, posing a pressing challenge for \textit{generalizable forensics}, \ie, detecting a wide range of unseen DeepFake types…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Yuezun Li , Delong Zhu , Xinjie Cui , Siwei Lyu

This paper reviews the state-of-the-art in deepfake generation and detection, focusing on modern deep learning technologies and tools based on the latest scientific advancements. The rise of deepfakes, leveraging techniques like Variational…

Cryptography and Security · Computer Science 2025-01-14 Arash Dehghani , Hossein Saberi

Recent rapid advancements in deepfake technology have allowed the creation of highly realistic fake media, such as video, image, and audio. These materials pose significant challenges to human authentication, such as impersonation,…

Cryptography and Security · Computer Science 2023-09-12 Binh Le , Shahroz Tariq , Alsharif Abuadbba , Kristen Moore , Simon Woo

DeepFakes pose a significant threat to our society. One representative DeepFake application is face-swapping, which replaces the identity in a facial image with that of a victim. Although existing methods partially mitigate these risks by…

Cryptography and Security · Computer Science 2025-02-18 Li Wang , Zheng Li , Xuhong Zhang , Shouling Ji , Shanqing Guo

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
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