A Robust Approach to Multimodal Deepfake Detection. [PDF]
J Imaging, 2023 Salvi D +6 more
europepmc +1 more source
An Improved Deepfake Detection Approach Using Hybrid Architecture Based on EfficientNet and Vision Transformer. [PDF]
J ImagingBanimelhem O, Alsharu AO.
europepmc +1 more source
Towards Generalizable Deepfake Detection: An Inconsistency-Aware Vision-Language Model Tuning Approach. [PDF]
Sensors (Basel)Zhang L, Peng S, Xu M, Lu T.
europepmc +1 more source
On the Generalization of Deep Learning Models in Video Deepfake Detection. [PDF]
J Imaging, 2023 Coccomini DA +3 more
europepmc +1 more source
FreqMamba: Spatial-Frequency Fusion and State Space Sequence Modeling for Deepfake Detection. [PDF]
Sensors (Basel)Li Z, Chen Y, Li M, Wang R, Liu H.
europepmc +1 more source
The Face Deepfake Detection Challenge. [PDF]
J Imaging, 2022 Guarnera L +19 more
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Analyzing DeepFake Detection Methods
, 2019 Deep learning has rate of success in solving various different complex problems including data analytics, human level control and computer vision. However, the advancement in deep learning have created different software which has caused many threats to ...
Memon, Muhammad Ahmed
core
Attention-augmented hybrid framework with evolutionary optimization for robust deepfake detection. [PDF]
Sci RepShivaprakash SJ, H S, Chauhan A, Md AQ.
europepmc +1 more source
Local attention and long-distance interaction of rPPG for deepfake detection. [PDF]
Vis Comput, 2023 Wu J, Zhu Y, Jiang X, Liu Y, Lin J.
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VerbaFake, EchoFake, and PixelFake: lightweight architectures with advanced augmentation for unimodal deepfake detection. [PDF]
Sci RepAli U +5 more
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