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Recent advances in AIGC have exacerbated the misuse of malicious deepfake content, making the development of reliable deepfake detection methods an essential means to address this challenge. Although existing deepfake detection models…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Changtao Miao , Yi Zhang , Weize Gao , Zhiya Tan , Weiwei Feng , Man Luo , Jianshu Li , Ajian Liu , Yunfeng Diao , Qi Chu , Tao Gong , Zhe Li , Weibin Yao , Joey Tianyi Zhou

Deep learning has received increasing interests in face recognition recently. Large quantities of deep learning methods have been proposed to handle various problems appeared in face recognition. Quite a lot deep methods claimed that they…

Computer Vision and Pattern Recognition · Computer Science 2023-07-07 Na Zhang

Deepfake defense not only requires the research of detection but also requires the efforts of generation methods. However, current deepfake methods suffer the effects of obscure workflow and poor performance. To solve this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Ivan Perov , Daiheng Gao , Nikolay Chervoniy , Kunlin Liu , Sugasa Marangonda , Chris Umé , Dpfks , Carl Shift Facenheim , Luis RP , Jian Jiang , Sheng Zhang , Pingyu Wu , Bo Zhou , Weiming Zhang

Deepfake technology is rapidly advancing, posing significant challenges to the detection of manipulated media content. Parallel to that, some adversarial attack techniques have been developed to fool the deepfake detectors and make…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Davide Alessandro Coccomini , Roberto Caldelli , Giuseppe Amato , Fabrizio Falchi , Claudio Gennaro

We share our experience with the recently released WILDS benchmark, a collection of ten datasets dedicated to developing models and training strategies which are robust to domain shifts. Several experiments yield a couple of critical…

Machine Learning · Computer Science 2022-01-03 Kazuki Irie , Imanol Schlag , Róbert Csordás , Jürgen Schmidhuber

Facial Expression Recognition is an active area of research in computer vision with a wide range of applications. Several approaches have been developed to solve this problem for different benchmark datasets. However, Facial Expression…

Computer Vision and Pattern Recognition · Computer Science 2016-01-12 Abubakrelsedik Karali , Ahmad Bassiouny , Motaz El-Saban

In recent years, as various realistic face forgery techniques known as DeepFake improves by leaps and bounds,more and more DeepFake detection techniques have been proposed. These methods typically rely on detecting statistical differences…

Computer Vision and Pattern Recognition · Computer Science 2023-04-25 Yang Hou , Qing Guo , Yihao Huang , Xiaofei Xie , Lei Ma , Jianjun Zhao

Modern T2V/I2V generators synthesize people increasingly hard to distinguish from authentic footage, while current evaluation suites lag: legacy benchmarks target manipulation-based forgeries, and recent synthetic-video benchmarks…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Roberto Leotta , Salvatore Alfio Sambataro , Claudio Vittorio Ragaglia , Mirko Casu , Yuri Petralia , Francesco Guarnera , Luca Guarnera , Sebastiano Battiato

The growing prevalence of speech deepfakes has raised serious concerns, particularly in real-world scenarios such as telephone fraud and identity theft. While many anti-spoofing systems have demonstrated promising performance on…

Audio and Speech Processing · Electrical Eng. & Systems 2026-05-12 Tong Zhang , Yihuan Huang , Yanzhen Ren

The rise of deepfake images, especially of well-known personalities, poses a serious threat to the dissemination of authentic information. To tackle this, we present a thorough investigation into how deepfakes are produced and how they can…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Haixu Song , Shiyu Huang , Yinpeng Dong , Wei-Wei Tu

In recent years, remarkable advancements in deep-fake generation technology have led to unprecedented leaps in its realism and capabilities. Despite these advances, we observe a notable lack of structured and deep analysis deepfake…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Tharindu Fernando , Darshana Priyasad , Sridha Sridharan , Arun Ross , Clinton Fookes

With the spread of DeepFake techniques, this technology has become quite accessible and good enough that there is concern about its malicious use. Faced with this problem, detecting forged faces is of utmost importance to ensure security…

Computer Vision and Pattern Recognition · Computer Science 2022-09-29 Gustavo Cunha Lacerda , Raimundo Claudio da Silva Vasconcelos

This demonstration paper presents $\mathbf{LayLens}$, a tool aimed to make deepfake understanding easier for users of all educational backgrounds. While prior works often rely on outputs containing technical jargon, LayLens bridges the gap…

Multimedia · Computer Science 2025-08-13 Abhijeet Narang , Parul Gupta , Liuyijia Su , Abhinav Dhall

Recent progress in audio generation has made it increasingly easy to create highly realistic environmental soundscapes, which can be misused to produce deceptive content, such as fake alarms, gunshots, and crowd sounds, raising concerns for…

Sound · Computer Science 2026-03-10 Han Yin , Yang Xiao , Rohan Kumar Das , Jisheng Bai , Ting Dang

Vulnerability detection is crucial to protect software security. Nowadays, deep learning (DL) is the most promising technique to automate this detection task, leveraging its superior ability to extract patterns and representations within…

Software Engineering · Computer Science 2026-02-13 Yuejun Guo , Qiang Hu , Qiang Tang , Yves Le Traon

In this paper we propose a new framework for evaluating the performance of explanation methods on the decisions of a deepfake detector. This framework assesses the ability of an explanation method to spot the regions of a fake image with…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Konstantinos Tsigos , Evlampios Apostolidis , Spyridon Baxevanakis , Symeon Papadopoulos , Vasileios Mezaris

Collecting and annotating real-world data for the development of object detection models is a time-consuming and expensive process. In the military domain in particular, data collection can also be dangerous or infeasible. Training models…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Frank A. Ruis , Alma M. Liezenga , Friso G. Heslinga , Luca Ballan , Thijs A. Eker , Richard J. M. den Hollander , Martin C. van Leeuwen , Judith Dijk , Wyke Huizinga

The rapid advancement of fake voice generation technology has ignited a race with detection systems, creating an urgent need to secure the audio ecosystem. However, existing benchmarks suffer from a critical limitation: they typically…

Sound · Computer Science 2025-10-20 Xutao Mao , Ke Li , Cameron Baird , Ezra Xuanru Tao , Dan Lin

Speech deepfake detection has achieved remarkable success in clean environments but faces significant challenges in complex, real-world scenarios where speech is often mixed with background music or noise. Current state-of-the-art methods…

Sound · Computer Science 2026-05-25 Qingcao Li , Yipeng Lin , Weichen Lian , Zhongjie Ba , Peng Cheng , Zhichao Lian

Recent advances in deep learning have led to substantial improvements in deepfake generation, resulting in fake media with a more realistic appearance. Although deepfake media have potential application in a wide range of areas and are…

Computer Vision and Pattern Recognition · Computer Science 2022-02-15 Trung-Nghia Le , Huy H Nguyen , Junichi Yamagishi , Isao Echizen
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