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20192023
most citedHierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition

58 citations · 87 across the 7 of their papers we have counts for

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8 papers · 1 filter

cs.CV20232 cited

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…

cs.CV20231 cited

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…

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.CV20224 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…

cs.CV202158 cited

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…

cs.CV2021

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…