20 citations · 20 across the 4 of their papers we have counts for
4 papers
PIE: Physics-inspired Low-light Enhancement
Dong Liang, Zhengyan Xu, Ling Li +2
In this paper, we propose a physics-inspired contrastive learning paradigm for low-light enhancement, called PIE. PIE primarily addresses three issues: (i) To resolve the problem o…
ALL-E: Aesthetics-guided Low-light Image Enhancement
Ling Li, Dong Liang, Yuanhang Gao +2
Evaluating the performance of low-light image enhancement (LLE) is highly subjective, thus making integrating human preferences into image enhancement a necessity. Existing methods…
Semantically Contrastive Learning for Low-light Image Enhancement
Dong Liang, Ling Li, Mingqiang Wei +5
Low-light image enhancement (LLE) remains challenging due to the unfavorable prevailing low-contrast and weak-visibility problems of single RGB images. In this paper, we respond to…
Active Terahertz Imaging Dataset for Concealed Object Detection
Dong Liang, Fei Xue, Ling Li
Concealed object detection in Terahertz imaging is an urgent need for public security and counter-terrorism. In this paper, we provide a public dataset for evaluating multi-object…