TY - GEN
T1 - Deep Learning for Visual Data Compression
AU - Lu, Guo
AU - Yang, Ren
AU - Wang, Shenlong
AU - Liu, Shan
AU - Timofte, Radu
N1 - Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/10/17
Y1 - 2021/10/17
N2 - In this paper, we will introduce the recent progress in deep learning based visual data compression, including image compression, video compression and point cloud compression. In the past few years, deep learning techniques have been successfully applied to various computer vision and image processing applications. However, for the data compression task, the traditional approaches (i.e., block based motion estimation and motion compensation, etc.) are still widely employed in the mainstream codecs. Considering the powerful representation capability of neural networks, it is feasible to improve the data compression performance by employing the advanced deep learning technologies. To this end, the deep leaning based compression approaches have recently received increasing attention from both academia and industry in the field of computer vision and signal processing.
AB - In this paper, we will introduce the recent progress in deep learning based visual data compression, including image compression, video compression and point cloud compression. In the past few years, deep learning techniques have been successfully applied to various computer vision and image processing applications. However, for the data compression task, the traditional approaches (i.e., block based motion estimation and motion compensation, etc.) are still widely employed in the mainstream codecs. Considering the powerful representation capability of neural networks, it is feasible to improve the data compression performance by employing the advanced deep learning technologies. To this end, the deep leaning based compression approaches have recently received increasing attention from both academia and industry in the field of computer vision and signal processing.
KW - image compression
KW - point cloud compression
KW - video compression
UR - http://www.scopus.com/inward/record.url?scp=85119321994&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85119321994&partnerID=8YFLogxK
U2 - 10.1145/3474085.3478877
DO - 10.1145/3474085.3478877
M3 - Conference contribution
AN - SCOPUS:85119321994
T3 - MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia
SP - 5683
EP - 5685
BT - MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia
PB - Association for Computing Machinery
T2 - 29th ACM International Conference on Multimedia, MM 2021
Y2 - 20 October 2021 through 24 October 2021
ER -