289 citations · 1.5k across the 44 of their papers we have counts for
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TDAN: Temporally Deformable Alignment Network for Video Super-Resolution
Yapeng Tian, Yulun Zhang, Yun Fu +1
Video super-resolution (VSR) aims to restore a photo-realistic high-resolution (HR) video frame from both its corresponding low-resolution (LR) frame (reference frame) and multiple…
Residual Dense Network for Image Restoration
Yulun Zhang, Yapeng Tian, Yu Kong +2
Convolutional neural network has recently achieved great success for image restoration (IR) and also offered hierarchical features. However, most deep CNN based IR models do not ma…
Channel Splitting Network for Single MR Image Super-Resolution
Xiaole Zhao, Yulun Zhang, Tao Zhang +1
High resolution magnetic resonance (MR) imaging is desirable in many clinical applications due to its contribution to more accurate subsequent analyses and early clinical diagnoses…
Support Neighbor Loss for Person Re-Identification
Kai Li, Zhengming Ding, Kunpeng Li +2
Person re-identification (re-ID) has recently been tremendously boosted due to the advancement of deep convolutional neural networks (CNN). The majority of deep re-ID methods focus…
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
Yulun Zhang, Kunpeng Li, Kai Li +3
Convolutional neural network (CNN) depth is of crucial importance for image super-resolution (SR). However, we observe that deeper networks for image SR are more difficult to train…
Residual Dense Network for Image Super-Resolution
Yulun Zhang, Yapeng Tian, Yu Kong +2
A very deep convolutional neural network (CNN) has recently achieved great success for image super-resolution (SR) and offered hierarchical features as well. However, most deep CNN…