1 citations · 2 across the 7 of their papers we have counts for
5 papers · 2 filters
ELVIS: Enhance Low-Light for Video Instance Segmentation in the Dark
Joanne Lin, Ruirui Lin, Yini Li +2
Video instance segmentation (VIS) for low-light content remains highly challenging for both humans and machines alike, due to noise, blur and other adverse conditions. The lack of…
NTIRE 2025 Challenge on Low Light Image Enhancement: Methods and Results
Xiaoning Liu, Zongwei Wu, Florin-Alexandru Vasluianu +102
This paper presents a comprehensive review of the NTIRE 2025 Low-Light Image Enhancement (LLIE) Challenge, highlighting the proposed solutions and final outcomes. The objective of…
Dynamic Weight-based Temporal Aggregation for Low-light Video Enhancement Under Extreme Noise
Ruirui Lin, Guoxi Huang, Nantheera Anantrasirichai
Low-light video enhancement (LLVE) is challenging due to noise, low contrast, and color degradation. While learning-based methods enable fast inference, they often fail under heavy…
Towards a General-Purpose Zero-Shot Synthetic Low-Light Image and Video Pipeline
Joanne Lin, Crispian Morris, Ruirui Lin +3
Low-light conditions pose significant challenges for both human and machine annotation. This in turn has led to a lack of research into machine understanding for low-light images a…
Bayesian Neural Networks for One-to-Many Mapping in Image Enhancement
Guoxi Huang, Qirui Yang, Ruirui Lin +3
In image enhancement tasks, such as low-light and underwater image enhancement, a degraded image can correspond to multiple plausible target images due to dynamic photography condi…