Nov 21, 2015 � This work presents a novel CU size classifier comprising an offline-trained decision tree with three hierarchical nodes.

To alleviate the intra encoding complexity and facilitate the real-time implementation, we use a machine learning technique: the random forests, for training.

This paper suggests a fast CU partitioning algorithm for Intra-only (All Intra) configuration. The proposal aims to early terminate CU partitioning for�...

Nov 21, 2015 � This paper proposes a method for complexity reduction in practical video encoders using multiple decision tree classifiers. The method is�...

Hence, this paper presents a mechanism that can be used by the RDO algorithm to select the optimal coding block size for Intra-Prediction, by using a data�...

A fast CU partition decision algorithm for VVC intra coding based on an MET-CNN is proposed. The algorithm can predict all partition information of a CU with a�...

This book discusses computational complexity of High Efficiency Video Coding (HEVC) encoders with coverage extending from the analysis of HEVC compression�...

The Bayesian decision model is used to classify the CUs into split and non-split classes thus to speed up the CU size decision process.

Sep 15, 2023 � This paper proposes a method that combines convolutional neural networks (CNN) with joint texture recognition to reduce encoding complexity.

Jun 8, 2020 � A fast algorithm for intra prediction mode selection based on mode grouping is proposed by reducing the number of modes entering rough mode decision.