4 papers
OmniLight: One Model to Rule All Lighting Conditions
Youngjin Oh, Junyoung Park, Junhyeong Kwon +1
Adverse lighting conditions, such as cast shadows and irregular illumination, pose significant challenges to computer vision systems by degrading visibility and color fidelity. Con…
TM-BSN: Triangular-Masked Blind-Spot Network for Real-World Self-Supervised Image Denoising
Junyoung Park, Youngjin Oh, Nam Ik Cho
Blind-spot networks (BSNs) enable self-supervised image denoising by preventing access to the target pixel, allowing clean signal estimation without ground-truth supervision. Howev…
DarkVRAI: Capture-Condition Conditioning and Burst-Order Selective Scan for Low-light RAW Video Denoising
Youngjin Oh, Junhyeong Kwon, Junyoung Park +1
Low-light RAW video denoising is a fundamentally challenging task due to severe signal degradation caused by high sensor gain and short exposure times, which are inherently limited…
AIM 2025 Low-light RAW Video Denoising Challenge: Dataset, Methods and Results
Alexander Yakovenko, George Chakvetadze, Ilya Khrapov +17
This paper reviews the AIM 2025 (Advances in Image Manipulation) Low-Light RAW Video Denoising Challenge. The task is to develop methods that denoise low-light RAW video by exploit…