Results 61 to 70 of about 130,964 (204)

Generalized Spoof Detection and Incremental Algorithm Recognition for Voice Spoofing

Applied Sciences, 2023
Highly deceptive deepfake technologies have caused much controversy, e.g., artificial intelligence-based software can automatically generate nude photos and deepfake images of anyone. This brings considerable threats to both individuals and society.
Jinlin Guo, Yancheng Zhao, Haoran Wang
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DIFLD: domain invariant feature learning to detect low-quality compressed face forgery images

Complex & Intelligent Systems, 2023
With the rapid development of deep learning, face forgery detection methods have also achieved remarkable progress. However, most methods suffer significant performance degradation on low-quality compressed face images.
Yan Zou, Chaoyang Luo, Jianxun Zhang
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Contrastive learning-based general Deepfake detection with multi-scale RGB frequency clues

Journal of King Saud University: Computer and Information Sciences, 2023
Deepfake is a type of image and video face manipulation methods which could cause security and society threats. Although some related databases and detection models have been proposed for detecting face forgery media, achieving a generalizable detector ...
Fengkai Dong, Xiaoqiang Zou, Jiahui Wang, Xiyao Liu   +3 more
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Picasso, Matisse, or a Fake? Automated Analysis of Drawings at the Stroke Level for Attribution and Authentication

, 2017
This paper proposes a computational approach for analysis of strokes in line drawings by artists. We aim at developing an AI methodology that facilitates attribution of drawings of unknown authors in a way that is not easy to be deceived by forged art ...
Elgammal, Ahmed, Kang, Yan, Leeuw, Milko Den   +2 more
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Mf-net: multi-feature fusion network based on two-stream extraction and multi-scale enhancement for face forgery detection

Complex & Intelligent Systems
Due to the increasing sophistication of face forgery techniques, the images generated are becoming more and more realistic and difficult for human eyes to distinguish.
Hanxian Duan, Qian Jiang, Xin Jin, Michal Wozniak, Yi Zhao, Liwen Wu, Shaowen Yao, Wei Zhou   +7 more
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TVN: Detect Deepfakes Images using Texture Variation Network

Inteligencia Artificial, 2023
Face manipulation technology is rapidly developing, making it impossible for human eyes to recognize fake face photos. Convolutional Neural Network (CNN) discriminators, on the other hand, can fast achieve high accuracy in distinguishing fake/real face ...
Haseena S, Saroja S, Shri Dharshini D, Nivetha A.   +3 more
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Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries

, 2019
With advanced image journaling tools, one can easily alter the semantic meaning of an image by exploiting certain manipulation techniques such as copy-clone, object splicing, and removal, which mislead the viewers.
Bappy, Jawadul H., Manjunath, B. S., Nataraj, Lakshmanan, Roy-Chowdhury, Amit K., Simons, Cody   +4 more
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PIANO: Proximity-based User Authentication on Voice-Powered Internet-of-Things Devices

, 2017
Voice is envisioned to be a popular way for humans to interact with Internet-of-Things (IoT) devices. We propose a proximity-based user authentication method (called PIANO) for access control on such voice-powered IoT devices.
Bao, Xuan, Cao, Xiaoyu, Gong, Neil Zhenqiang, Jin, Hongxia, Ozen, Altay, Shin, Richard, Song, Dawn, Wu, Yu   +7 more
core   +1 more source

MDCF-Net: Multi-Scale Dual-Branch Network for Compressed Face Forgery Detection

IEEE Access
Face forgery detection aims to identify manipulated or altered facial images or videos created using artificial intelligence. Existing detection methods exhibit favorable performance on high-quality videos, but the videos in daily applications are ...
Jiting Zhou, Xinrui Zhao, Qian Xu, Pu Zhang, Zhihao Zhou   +4 more
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SHIELD: an evaluation benchmark for face spoofing and forgery detection with multimodal large language models

Visual Intelligence
Multimodal large language models (MLLMs) have demonstrated strong capabilities in vision-related tasks, capitalizing on their visual semantic comprehension and reasoning capabilities.
Yichen Shi, Yuhao Gao, Yingxin Lai, Hongyang Wang, Jun Feng, Lei He, Jun Wan, Changsheng Chen, Zitong Yu, Xiaochun Cao   +9 more
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