Reduction of Video Compression Artifacts Based on Deep Temporal Networks
It has been shown that deep convolutional neural networks (CNNs) reduce JPEG compression artifacts better than the previous approaches. However, the latest video compression standards have more complex artifacts than the JPEG, including the flickering which is not well reduced by the CNN-based metho...
Main Authors: | Jae Woong Soh, Jaewoo Park, Yoonsik Kim, Byeongyong Ahn, Hyun-Seung Lee, Young-Su Moon, Nam Ik Cho |
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Format: | Article |
Language: | English |
Published: |
IEEE
2018-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8502045/ |
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