167 citations · 370 across the 17 of their papers we have counts for
5 papers · 1 filter
Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid Network
Wenjie Li, Juncheng Li, Guangwei Gao +4
Lightweight image super-resolution aims to reconstruct high-resolution images from low-resolution images using low computational costs. However, existing methods result in the loss…
Cross-receptive Focused Inference Network for Lightweight Image Super-Resolution
Wenjie Li, Juncheng Li, Guangwei Gao +3
Recently, Transformer-based methods have shown impressive performance in single image super-resolution (SISR) tasks due to the ability of global feature extraction. However, the ca…
Multiple Degradation and Reconstruction Network for Single Image Denoising via Knowledge Distillation
Juncheng Li, Hanhui Yang, Qiaosi Yi +4
Single image denoising (SID) has achieved significant breakthroughs with the development of deep learning. However, the proposed methods are often accompanied by plenty of paramete…
Lightweight Bimodal Network for Single-Image Super-Resolution via Symmetric CNN and Recursive Transformer
Guangwei Gao, Zhengxue Wang, Juncheng Li +3
Single-image super-resolution (SISR) has achieved significant breakthroughs with the development of deep learning. However, these methods are difficult to be applied in real-world…
CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-Resolution
Guangwei Gao, Zixiang Xu, Juncheng Li +3
Recently, deep convolution neural networks (CNNs) steered face super-resolution methods have achieved great progress in restoring degraded facial details by jointly training with f…