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20182023
most citedCTCNet: A CNN-Transformer Cooperation Network for Face Image Super-Resolution

167 citations · 367 across the 27 of their papers we have counts for

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Showing 2022Show all

8 papers · 1 filter

cs.CV2022★ 5 cited

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…

eess.SY2022★ 1 cited

Quantized Consensus under Data-Rate Constraints and DoS Attacks: A Zooming-In and Holding Approach

Maopeng Ran, Shuai Feng, Juncheng Li +1

This paper is concerned with the quantized consensus problem for uncertain nonlinear multi-agent systems under data-rate constraints and Denial-of-Service (DoS) attacks. The agents…

cs.CV2022★ 2 cited

Snow Mask Guided Adaptive Residual Network for Image Snow Removal

Bodong Cheng, Juncheng Li, Ying Chen +2

Image restoration under severe weather is a challenging task. Most of the past works focused on removing rain and haze phenomena in images. However, snow is also an extremely commo…

cs.CV2022★ 4 cited

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…

cs.CV2022

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…

cs.CV2022★ 4 cited

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…