5 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…
DINOLight: Robust Ambient Light Normalization with Self-supervised Visual Prior Integration
Youngjin Oh, Junhyeong Kwon, Nam Ik Cho
This paper presents a new ambient light normalization framework, DINOLight, that integrates the self-supervised model DINOv2's image understanding capability into the restoration p…
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…
Towards Controllable Real Image Denoising with Camera Parameters
Youngjin Oh, Junhyeong Kwon, Keuntek Lee +1
Recent deep learning-based image denoising methods have shown impressive performance; however, many lack the flexibility to adjust the denoising strength based on the noise levels,…
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…