The study introduces a new face swapping method leveraging the progressively growing structure of a pre-trained StyleGAN. Instead of the traditional encoder-decoder structures and embedding integration networks, this method disentangles…
Continue readingThe article presents a novel approach to Unsupervised Domain Adaptation (UDA) called Invariant Consistency Learning (ICON). Traditional UDA methods often suffer from spurious correlations between domain-invariant and domain-specific features, which…
Continue readingThe “3D-IDS: Doubly Disentangled Dynamic Intrusion Detection” study developed by a team from the Beijing University of Posts and Telecommunications presents a novel method that aims to enhance network intrusion…
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