167 citations · 370 across the 17 of their papers we have counts for
17 papers
EWT: Efficient Wavelet-Transformer for Single Image Denoising
Juncheng Li, Bodong Cheng, Ying Chen +2
Transformer-based image denoising methods have achieved encouraging results in the past year. However, it must uses linear operations to model long-range dependencies, which greatl…
PFT-SSR: Parallax Fusion Transformer for Stereo Image Super-Resolution
Hansheng Guo, Juncheng Li, Guangwei Gao +2
Stereo image super-resolution aims to boost the performance of image super-resolution by exploiting the supplementary information provided by binocular systems. Although previous m…
Lightweight Real-time Semantic Segmentation Network with Efficient Transformer and CNN
Guoan Xu, Juncheng Li, Guangwei Gao +3
In the past decade, convolutional neural networks (CNNs) have shown prominence for semantic segmentation. Although CNN models have very impressive performance, the ability to captu…
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…
Feature Distillation Interaction Weighting Network for Lightweight Image Super-Resolution
Guangwei Gao, Wenjie Li, Juncheng Li +3
Convolutional neural networks based single-image super-resolution (SISR) has made great progress in recent years. However, it is difficult to apply these methods to real-world scen…
FBSNet: A Fast Bilateral Symmetrical Network for Real-Time Semantic Segmentation
Guangwei Gao, Guoan Xu, Juncheng Li +3
Real-time semantic segmentation, which can be visually understood as the pixel-level classification task on the input image, currently has broad application prospects, especially i…
Hierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition
Guangwei Gao, Yi Yu, Jian Yang +2
Cross-resolution face recognition (CRFR), which is important in intelligent surveillance and biometric forensics, refers to the problem of matching a low-resolution (LR) probe face…
Leaning Compact and Representative Features for Cross-Modality Person Re-Identification
Guangwei Gao, Hao Shao, Fei Wu +2
This paper pays close attention to the cross-modality visible-infrared person re-identification (VI Re-ID) task, which aims to match pedestrian samples between visible and infrared…
JDSR-GAN: Constructing An Efficient Joint Learning Network for Masked Face Super-Resolution
Guangwei Gao, Lei Tang, Fei Wu +2
With the growing importance of preventing the COVID-19 virus, face images obtained in most video surveillance scenarios are low resolution with mask simultaneously. However, most o…
MSCFNet: A Lightweight Network With Multi-Scale Context Fusion for Real-Time Semantic Segmentation
Guangwei Gao, Guoan Xu, Yi Yu +3
In recent years, how to strike a good trade-off between accuracy and inference speed has become the core issue for real-time semantic segmentation applications, which plays a vital…
Lightweight Image Super-Resolution with Multi-scale Feature Interaction Network
Zhengxue Wang, Guangwei Gao, Juncheng Li +2
Recently, the single image super-resolution (SISR) approaches with deep and complex convolutional neural network structures have achieved promising performance. However, those meth…
Cross-View Image Synthesis with Deformable Convolution and Attention Mechanism
Hao Ding, Songsong Wu, Hao Tang +3
Learning to generate natural scenes has always been a daunting task in computer vision. This is even more laborious when generating images with very different views. When the views…
LEDNet: A Lightweight Encoder-Decoder Network for Real-Time Semantic Segmentation
Yu Wang, Quan Zhou, Jia Liu +4
The extensive computational burden limits the usage of CNNs in mobile devices for dense estimation tasks. In this paper, we present a lightweight network to address this problem,na…