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Found 5 papers, 3 papers with code
Two-stage Progressive Residual Dense Attention Network for Image Denoising
Deep convolutional neural networks (CNNs) for image denoising can effectively exploit rich hierarchical features and have achieved great success.
Dual Residual Attention Network for Image Denoising
The proposed DRANet includes two different parallel branches, which can capture complementary features to enhance the learning ability of the model.
Ranked #1 on
Image Denoising
on SIDD
(Average PSNR metric)
Image Blind Denoising Using Dual Convolutional Neural Network with Skip Connection
The proposed DCBDNet consists of a noise estimation network and a dual convolutional neural network (CNN).
DCANet: Dual Convolutional Neural Network with Attention for Image Blind Denoising
In this paper, we present a new dual convolutional neural network (CNN) with attention for image blind denoising, named as the DCANet.
Mirror-Yolo: An attention-based instance segmentation and detection model for mirrors
Mirrors can degrade the performance of computer vision models, however to accurately detect mirrors in images remains challenging.
