Wide Activated Separate 3D Convolution for Video Super-Resolution
Video super-resolution (VSR) aims to recover a realistic high-resolution (HR) frame from its corresponding center low-resolution (LR) frame and several neighbouring supporting frames. The neighbouring supporting LR frames can provide extra information to help recover the HR frame. However, these fr...
Main Author: | Yu, Xiafei |
---|---|
Other Authors: | Zhao, Jiying |
Format: | Others |
Language: | en |
Published: |
Université d'Ottawa / University of Ottawa
2019
|
Subjects: | |
Online Access: | http://hdl.handle.net/10393/39974 http://dx.doi.org/10.20381/ruor-24213 |
Similar Items
-
Multi-Kernel Deformable 3D Convolution for Video Super-Resolution
by: Dou, Tianyu
Published: (2021) -
Depth Map Super-Resolution Using Guided Deformable Convolution
by: Joon-Yeon Kim, et al.
Published: (2021-01-01) -
Video Super-Resolution via Residual Learning
by: Wenjun Wang, et al.
Published: (2018-01-01) -
Color-Guided Depth Map Super Resolution Using Convolutional Neural Network
by: Min Ni, et al.
Published: (2017-01-01) -
Super-resolution reconstruction of a digital elevation model based on a deep residual network
by: Jiao Donglai, et al.
Published: (2020-11-01)