A Novel Deep Learning-Based Method of Improving Coding Efficiency from the Decoder-End for HEVC

By Tingting Wang, Mingjin Chen, Hongyang Chao. 2017

177 citations recorded by the source corpus.

Subfields: Computational Mechanics, 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 Computational Mechanics

1. Xiaodan Song
2. Mai Xu
3. Oren Rippel
4. Lubomir D. Bourdev
5. Zulin Wang
6. Shiliang Pu
7. Ren Yang

In Computer Vision and Pattern Recognition

1. Luc Van Gool
2. Trevor Darrell
3. Dacheng Tao
4. Jitendra Malik
5. Xiaogang Wang
6. Li Fei-Fei
7. Ming-Hsuan Yang
8. Andrew Zisserman

In Signal Processing

1. Mai Xu
2. Zulin Wang
3. Ren Yang
4. Tianyi Li
5. Xiaodan Song
6. Oren Rippel
7. Lubomir D. Bourdev
8. Steve Branson

Citations in the corpus

• Learned Video Compression (2018, background): “These include improved motion compensation and interpolation [49, 16, 53, 26], intra-prediction coding [35], post-processing refinement [7, 50, 21, 51, 43, 52, 36, 14], and rate control [23].”
• Enhancing Quality for HEVC Compressed Videos (2017, methodology): “Therefore, the network of [17] is not able to deal with both intra-and inter-coding distortion, because there is no specific design for I and P/B frames, respectively.”
• Multi-frame Quality Enhancement for Compressed Video (2018, methodology): “More importantly, the video encoder does not need to be modified when applying the DCAD [34] and DSCNN [38] approaches.”
• A Practical Convolutional Neural Network as Loop Filter for Intra Frame (2018, background): “Recent research has investigated the deep learning approach, especially convolutional neural network (CNN), on post-processing [3, 4, 5, 6] or loop filtering [7, 8].”