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CRISP: Progressive Illumination Curriculum for Recurrent Low-Light Video Enhancement with Semantic Priors
Ruirui Lin, Xin Yan Lim, Yini Li +2
Low-light video enhancement requires the recovery of brightness, color, and fine spatial structures while preserving temporal coherence in the presence of noise and motion. Existin…
PixIE: Prompted Pixel-Space Low-Light Image Enhancement
Ruirui Lin, Guoxi Huang, David Bull +1
Low-light images suffer from severe noise, contrast loss, and semantic ambiguity, making enhancement a joint problem of denoising and detail recovery. We propose PixIE, a feed-forw…
BVI-Mamba: Video Enhancement Using a Visual State-Space Model for Low-Light and Underwater Environments
Guoxi Huang, Ruirui Lin, Yini Li +2
Videos captured in low-light and underwater conditions often suffer from distortions such as noise, low contrast, color imbalance, and blur. These issues not only limit visibility…
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…
BVI-RLV: A Fully Registered Dataset for Low-Light Video Enhancement
Ruirui Lin, Guoxi Huang, Joanne Lin +4
Low-light videos often exhibit spatiotemporally incoherent noise, compromising visibility and degrading performance in computer vision applications. A major challenge for enhancing…
BVI-Lowlight: Fully Registered Benchmark Dataset for Low-Light Video Enhancement
Nantheera Anantrasirichai, Ruirui Lin, Alexandra Malyugina +1
Low-light videos often exhibit spatiotemporal incoherent noise, leading to poor visibility and compromised performance across various computer vision applications. One significant…