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
Adverse weather conditions, such as rain, fog, and snow, degrade visual information, posing significant challenges for image restoration frameworks that adapt across diverse scenarios. Unified models for weather removal often struggle to capture weather-specific details, while two-stage methods require additional train...
Youngmin Oh, Sungyoung Lee, MyeongAh Cho et al.· IEEE Transactions on Image P...· 0 citations
This article introduces variance-reduced consistency learning (vrCL), a novel distillation technique that enables stable and efficient training of consistency models without relying on teacher model evaluations, resulting in high computational efficiency and significantly reduced training time.
