Results 51 to 60 of about 4,896,353 (133)

Two-Stream Network for Face Forgery Detection Supervised by Single-Center Loss [PDF]

Jisuanji kexue yu tansuo
Deepfake techniques are becoming increasingly popular, triggering widespread social skepticism about the authenticity of information. The factors that limit the generalization of detectors are considered from the feature and learning levels: Firstly, CNN-
HU Siju, LU Tianliang, PENG Shufan, YANG Gang, YIN Haoran
doaj   +1 more source

DeepFake Detection Method Based on Multi-Scale Dual-Stream Network [PDF]

Jisuanji gongcheng
DeepFake-enabled abuse of face forgery technology has given rise to considerable security risks to society and individuals; therefore, DeepFake detection has become a hot topic of research. Current deep learning-based forgery detection techniques exhibit
JIANG Cuiling, CHENG Ziyuan, YU Xingui, WAN Yongjing
doaj   +1 more source

Face forgery video detection based on expression key sequences

Journal of King Saud University: Computer and Information Sciences
In order to minimize additional computational costs in detecting forged videos, and enhance detection accuracy, this paper employs dynamic facial expression sequences as key sequences, replacing original video sequences as inputs for the detection model.
Yameng Tu, Jianbin Wu, Liang Lu, Shuaikang Gao, MingHao Li   +4 more
doaj   +1 more source

Frame-wise Heterogeneous Deepfake Detection: Fine-Grained Multi-label Learning Framework [PDF]

Jisuanji kexue yu tansuo
The pervasive diffusion of Deepfake techniques has posed severe threats to public security and social trust. Videos forged by cascading multiple synthesis models or post-processing modules increasingly exhibit frame-different manipulative traces, a ...
ZOU Zhengrui, OU Wei, PANG Mengxue, AN Hongli, YUE Qiuling, HAN Wenbao
doaj   +1 more source

A hybrid technique for face detection in color images [PDF]

, 2005
In this paper, a hybrid technique for face detection in color images is presented. The proposed technique combines three analysis models, namely skin detection, automatic eye localization, and appearance-based face/nonface classification.
O'Connor, Noel E., Cooray, Saman H., O\u27Connor, Noel E., N. O'Connor, S. Cooray   +4 more
core   +2 more sources

Exploiting Facial Relationships and Feature Aggregation for Multi-Face Forgery Detection

, 2023
Face forgery techniques have emerged as a forefront concern, and numerous detection approaches have been proposed to address this challenge. However, existing methods predominantly concentrate on single-face manipulation detection, leaving the more ...
Li, Qian, Jingyi, Deng, Wang, Hang, Shen, Chao, Lin, Chenhao, Yi, Fangbin   +5 more
core  

Generalization challenges in video deepfake detection: methods, obstacles, and technological advances

大数据
With the rapid development of artificial intelligence, deepfake technology has become a powerful tool for generating realistic audio, images, and videos. However, its widespread use and decreasing costs pose serious threats to personal privacy and social
LI Junjie, WANG Jianzong, ZHANG Xulong, QU Xiaoyang   +3 more
doaj   +2 more sources

ENF Based Video Forgery Detection Algorithm

, 2020
The electric network frequency (ENF) is recorded in the videos taken under the lights powered by grid and can be used for digital forensics. However, due to the lack of data caused by the low frame rate of the video, the ENF-based forensics methods ...
Yufei Wang, Alan Liew, Wang, Y, Hu, Y, Liew, AWC, Yongjian Hu, Chang-Tsun Li, Li, CT   +7 more
core   +1 more source

Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection

The proliferation of face forgery techniques has raised significant concerns within society, thereby motivating the development of face forgery detection methods.
Jia, Xiaojun, Liang, Jiawei, Cao, Xiaochun, Liu, Aishan, Liang, Siyuan, Kuang, Junhao   +5 more
core  

AltFreezing for More General Video Face Forgery Detection

, 2023
Existing face forgery detection models try to discriminate fake images by detecting only spatial artifacts (e.g., generative artifacts, blending) or mainly temporal artifacts (e.g., flickering, discontinuity).
Wang, Zhendong, Li, Houqiang, Bao, Jianmin, Wang, Weilun, Zhou, Wengang   +4 more
core