Author

Beomyoung Kim

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Preprint Sep 2026

Less Supervision, Better Generalization: Weakly Supervised Fake Region Localization in Diffusion-Edited Images

Localizing AI-edited regions is essential for interpretable forensic analysis, but remains challenging due to subtle and spatially distributed artifacts that are misaligned with semantic or object boundaries. Existing approaches rely on pixel-level supervision from controlled editing pipelines, which is difficult to sc...

Junhee Lee, Donghyeon Jeon, Taeoh Kim et al. · 0 citations

Jul 2026

Learning from Adversity: Semantic-Aware Mask Refinement through Adversarial Perturbation

Phoenix is introduced, a novel framework that leverages adversarial learning to generate semantically meaningful noise patterns and contrastive learning to model refinement relationships that significantly outperforms existing methods across diverse tasks, while consistently enhancing state-of-the-art segmentation mode...

Beomyoung Kim, S. Hwang · arXiv.org · 0 citations