Log In Sign Up

Analytic Simplification of Neural Network based Intra-Prediction Modes for Video Compression

by   Maria Santamaria, et al.

With the increasing demand for video content at higher resolutions, it is evermore critical to find ways to limit the complexity of video encoding tasks in order to reduce costs, power consumption and environmental impact of video services. In the last few years, algorithms based on Neural Networks (NN) have been shown to benefit many conventional video coding modules. But while such techniques can considerably improve the compression efficiency, they usually are very computationally intensive. It is highly beneficial to simplify models learnt by NN so that meaningful insights can be exploited with the goal of deriving less complex solutions. This paper presents two ways to derive simplified intra-prediction from learnt models, and shows that these streamlined techniques can lead to efficient compression solutions.


Spatial Information Refinement for Chroma Intra Prediction in Video Coding

Video compression benefits from advanced chroma intra prediction methods...

MPEG-2 Prediction Residue Analysis

Based on the use of synthetic signals and autoregressive models to chara...

Attention-Based Neural Networks for Chroma Intra Prediction in Video Coding

Neural networks can be successfully used to improve several modules of a...

Chroma Intra Prediction with attention-based CNN architectures

Neural networks can be used in video coding to improve chroma intra-pred...

Neural Generation of Blocks for Video Coding

Well-trained generative neural networks (GNN) are very efficient at comp...

Tiny Video Networks

Video understanding is a challenging problem with great impact on the ab...