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Do Seung-hyeok Back

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Robust, Generalizable Proactive Face-Swapping Defense via Semantic Gradient Divergence

This work proposes a robust, generalizable proactive face-swapping defense via semantic gradient divergence (SGD-Guard), and introduces an integrated feature gallery that uses CLIP features and a generalized identity feature, obtained by iteratively refining heterogeneous identity features into a homogeneous representation.

Do Seung-hyeok Back, Hyun Ki, Juwan Kim et al. · 0 citations