AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
Overall, FAD-Net provides a task-oriented integration of frequency-aware feature fusion and dynamic feature refinement for image tampering localization, and achieves competitive F1 and IoU performance across the evaluated datasets, including post-processed scenarios.
An image tampering detection method based on two-branch gating-augmented Transformer encoder with attention-based feature fusion with the superiority of the proposed network is proposed.
The proposed MFEFN framework outperforms existing state-of-the-art methods, providing a new and effective perspective for spatiotemporal modeling in fake video detection.
With the continuous evolution of document forgery technology, high-quality tampering poses severe challenges to traditional detection methods based on single-domain statistics and edge structures. Therefore, the study proposes a method based on multi-transformation domain attention fusion and fine-grained artifact enha...
As information technology advances, digital content has become widely adopted across diverse fields such as news broadcasting, entertainment, commerce, and forensic investiga?tion. However, the availability of sophisticated multimedia editing tools has significantly increased the risk of video and image forgery, raisin...
This work extends an existing detector by introducing a unified multiclass framework for image authenticity, which incorporates a segmentation branch to enable pixel-level localization of tampered regions and outperforms selected recent benchmarks.
Although Transformer-based real-time object detectors have achieved promising performance in autonomous driving scenarios, their ability to detect small objects remains limited. This limitation primarily arises because small objects occupy only a few pixels in an image and contain weak edge and texture information, whi...
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