Title
Advanced ANN Architecture for the CTU Partitioning in All Intra HEVC
Authors
[ 1 ] Instytut Telekomunikacji Multimedialnej, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ S ] student | [ P ] employee
Scientific discipline (Law 2.0)
Year of publication
2025
Article type
scientific article
Publication language
english
Keywords
Abstract
EN Due to the growing complexity of video encoders, the optimization of the parameters of the encoding process is becoming an important issue. In recent years, this has become an important field of application of neural networks. Artificial neural networks in video encoders are used to accelerate the video encoder operation. This paper demonstrates the use of different ResNet- and DenseNet-type architectures to accelerate the CTU partitioning algorithm in HEVC in All Intra mode. The paper demonstrates the results of an exhaustive evaluation of different proposed architectures, considering compression efficiency, network size, and encoding time reduction. Multiple pros and cons of the proposed architectures are presented in the Conclusions, considering various limitations that may be important for a given application, like hardware-constrained sensor networks or standalone small devices operating with images and videos.
Date of online publication
26.09.2025
Pages (from - to)
5971-1 - 5971-16
Comments
Article number: 5971
License type
CC BY (attribution alone)
Open Access Mode
open journal
Open Access Text Version
final published version
Release date
26.09.2025
Date of Open Access to the publication
at the time of publication
Full text of article
Access level to full text
public
Ministry points / journal
100
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