AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
The Boundary-Guided Frequency Fusion framework for unified image-level detection and pixel-level localization of FAE is introduced, which provides stable semantic localization, while a DCT-based high-frequency branch offers complementary residual cues.
A unified multimodal forensic framework for joint image-authenticity detection and manipulation localization that integrates frequency-domain features cues with visual representations to improve manipulation-sensitive feature learning and an object-context mask-refinement module is introduced to enhance pixel-level loc...
The results demonstrate that the proposed experimental validation on benchmark datasets indicates improved detection accuracy, robustness to noise compression, and localization clarity when compared to conventional approaches.
FARM-FER is proposed, which treats local and global frequency descriptors as a control signal rather than an additional classifier input, supporting a lightweight yet effective design in terms of model size and arithmetic cost for noisy-label FER.
This work explores an approach that integrates wavelet-based frequency analysis with deep learning to enhance deepfake detection, and suggests that wavelet sub-bands expose manipulation cues that are useful for detecting unseen fake classes, but they should not be interpreted as a uniform robustness improvement.
The results show that clean-set performance is not a reliable indicator of robustness under compression, resizing, and blurring, and reinforce the need for degraded evaluation protocols and highlight self-supervised visual representations as a promising direction for robust face forgery detection.
Generalizable face forgery detection has become a critical problem in multimedia forensics as modern face manipulation techniques can generate increasingly realistic facial content. Vision foundation models provide a promising basis for this problem, but existing detectors usually rely on the last-layer visual feature,...
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