5 papers
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…
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…
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…
Unsupervised Methods for Video Quality Improvement: A Survey of Restoration and Enhancement Techniques
Alexandra Malyugina, Yini Li, Joanne Lin +1
Video restoration and enhancement are critical not only for improving visual quality, but also as essential pre-processing steps to boost the performance of a wide range of downstr…
Multi-Scale Denoising in the Feature Space for Low-Light Instance Segmentation
Joanne Lin, Nantheera Anantrasirichai, David Bull
Instance segmentation for low-light imagery remains largely unexplored due to the challenges imposed by such conditions, for example shot noise due to low photon count, color disto…