177 citations · 267 across the 12 of their papers we have counts for
7 papers · 1 filter
A cross Transformer for image denoising
Chunwei Tian, Menghua Zheng, Wangmeng Zuo +3
Deep convolutional neural networks (CNNs) depend on feedforward and feedback ways to obtain good performance in image denoising. However, how to obtain effective structural informa…
Multi-stage image denoising with the wavelet transform
Chunwei Tian, Menghua Zheng, Wangmeng Zuo +3
Deep convolutional neural networks (CNNs) are used for image denoising via automatically mining accurate structure information. However, most of existing CNNs depend on enlarging d…
A heterogeneous group CNN for image super-resolution
Chunwei Tian, Yanning Zhang, Wangmeng Zuo +3
Convolutional neural networks (CNNs) have obtained remarkable performance via deep architectures. However, these CNNs often achieve poor robustness for image super-resolution (SR)…
Generative Adversarial Networks for Image Super-Resolution: A Survey
Ziang Wu, Xuanyu Zhang, Yinbo Yu +3
Single image super-resolution (SISR) has played an important role in the field of image processing. Recent generative adversarial networks (GANs) can achieve excellent results on l…
Lightweight image super-resolution with enhanced CNN
Chunwei Tian, Ruibin Zhuge, Zhihao Wu +4
Deep convolutional neural networks (CNNs) with strong expressive ability have achieved impressive performances on single image super-resolution (SISR). However, their excessive amo…
Designing and Training of A Dual CNN for Image Denoising
Chunwei Tian, Yong Xu, Wangmeng Zuo +3
Deep convolutional neural networks (CNNs) for image denoising have recently attracted increasing research interest. However, plain networks cannot recover fine details for a comple…
Deep Learning on Image Denoising: An overview
Chunwei Tian, Lunke Fei, Wenxian Zheng +3
Deep learning techniques have received much attention in the area of image denoising. However, there are substantial differences in the various types of deep learning methods deali…