6 citations · 11 across the 7 of their papers we have counts for
7 papers
GT-Mean Loss: A Simple Yet Effective Solution for Brightness Mismatch in Low-Light Image Enhancement
Jingxi Liao, Shijie Hao, Richang Hong +1
Low-light image enhancement (LLIE) aims to improve the visual quality of images captured under poor lighting conditions. In supervised LLIE research, there exists a significant yet…
SDI-Net: Toward Sufficient Dual-View Interaction for Low-light Stereo Image Enhancement
Linlin Hu, Ao Sun, Shijie Hao +2
Currently, most low-light image enhancement methods only consider information from a single view, neglecting the correlation between cross-view information. Therefore, the enhancem…
Decoupled Low-light Image Enhancement
Shijie Hao, Xu Han, Yanrong Guo +1
The visual quality of photographs taken under imperfect lightness conditions can be degenerated by multiple factors, e.g., low lightness, imaging noise, color distortion and so on.…
Few-shot Learning with Global Relatedness Decoupled-Distillation
Yuan Zhou, Yanrong Guo, Shijie Hao +3
Despite the success that metric learning based approaches have achieved in few-shot learning, recent works reveal the ineffectiveness of their episodic training mode. In this paper…
Positive Sample Propagation along the Audio-Visual Event Line
Jinxing Zhou, Liang Zheng, Yiran Zhong +2
Visual and audio signals often coexist in natural environments, forming audio-visual events (AVEs). Given a video, we aim to localize video segments containing an AVE and identify…
A Survey on Large-scale Machine Learning
Meng Wang, Weijie Fu, Xiangnan He +2
Machine learning can provide deep insights into data, allowing machines to make high-quality predictions and having been widely used in real-world applications, such as text mining…
Real-time Semantic Segmentation via Spatial-detail Guided Context Propagation
Shijie Hao, Yuan Zhou, Yanrong Guo +3
Nowadays, vision-based computing tasks play an important role in various real-world applications. However, many vision computing tasks, e.g. semantic segmentation, are usually comp…