6 citations · 16 across the 5 of their papers we have counts for
4 papers · 1 filter
Two-stage Progressive Residual Dense Attention Network for Image Denoising
Wencong Wu, An Ge, Guannan Lv +3
Deep convolutional neural networks (CNNs) for image denoising can effectively exploit rich hierarchical features and have achieved great success. However, many deep CNN-based denoi…
Image Blind Denoising Using Dual Convolutional Neural Network with Skip Connection
Wencong Wu, Shicheng Liao, Guannan Lv +2
In recent years, deep convolutional neural networks have shown fascinating performance in the field of image denoising. However, deeper network architectures are often accompanied…
DCANet: Dual Convolutional Neural Network with Attention for Image Blind Denoising
Wencong Wu, Guannan Lv, Yingying Duan +3
Noise removal of images is an essential preprocessing procedure for many computer vision tasks. Currently, many denoising models based on deep neural networks can perform well in r…
Mirror-Yolo: A Novel Attention Focus, Instance Segmentation and Mirror Detection Model
Fengze Li, Jieming Ma, Zhongbei Tian +4
Mirrors can degrade the performance of computer vision models, but research into detecting them is in the preliminary phase. YOLOv4 achieves phenomenal results in terms of object d…