End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensation

5 January 2020

Xiaohong Liu

Lingshi Kong

Yang Zhou

Jiying Zhao

Jun Chen

SupR

Papers citing "End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensation"

3 / 3 papers shown

Title
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Wenzhe Shi Jose Caballero Ferenc Huszár J. Totz Andrew P. Aitken Rob Bishop Daniel Rueckert Zehan Wang SupR 19 4748 0 16 Sep 2016
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 34 14259 0 02 Nov 2015
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 24 7095 0 13 Jun 2015