Convolutional Neural Network-Based Motion Compensation Refinement for Video Coding
By Shuai Huo, Dong Liu, Feng Wu, Houqiang Li. 2018
41 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Ming-Hsuan Yang
- Trevor Darrell
- Dacheng Tao
- Jitendra Malik
- Xiaogang Wang
- Li Fei-Fei
- Andrew Zisserman
In Signal Processing
- Shanshe Wang
- Oren Rippel
- Lubomir D. Bourdev
- Shiqi Wang
- Siwei Ma
- Xinfeng Zhang
- Steve Branson
- Chuanmin Jia
Citations in the corpus
- Learned Video Compression (2018, background): “These include improved motion compensation and interpolation [54, 21, 58, 31], intra-prediction coding [40], post-processing refinement [7, 55, 26, 56, 48, 57, 41, 17], and rate control [28].”
- Image and Video Compression With Neural Networks: A Review (2019, methodology): “proposed a straightforward method [82] to improve inter prediction efficiency by utilizing the existing variable-filter-size residue-learning CNN (VRCNN) [83], which is named CNN-based motion compensation refinement (CNNMCR).”