3 papers
cs.CV2026
Continuous Degradation Modeling via Latent Flow Matching for Real-World Super-Resolution
Hyeonjae Kim, Dongjin Kim, Eugene Jin +1
While deep learning-based super-resolution (SR) methods have shown impressive outcomes with synthetic degradation scenarios such as bicubic downsampling, they frequently struggle t…
cs.CV2025
IDF: Iterative Dynamic Filtering Networks for Generalizable Image Denoising
Dongjin Kim, Jaekyun Ko, Muhammad Kashif Ali +1
Image denoising is a fundamental challenge in computer vision, with applications in photography and medical imaging. While deep learning-based methods have shown remarkable success…
cs.CV2025
Harnessing Meta-Learning for Controllable Full-Frame Video Stabilization
Muhammad Kashif Ali, Eun Woo Im, Dongjin Kim +4
Video stabilization remains a fundamental problem in computer vision, particularly pixel-level synthesis solutions for video stabilization, which synthesize full-frame outputs, add…