RESEARCH PAPER / Sep 2021
/
Video coding,
Compression,
Machine learning/ Deep learning /Artificial Intelligence Neural network
Despite many modern applications of Deep Neural Networks (DNNs), the large number of parameters in the hidden layers makes them unattractive for deployment on devices with storage capacity constraints. In this paper we propose a Data-Driven Low-rank (DDLR) method to reduce the number of parameters of pretrained DNNs and expedite...
RESEARCH PAPER / Aug 2021
/
Video coding,
Compression,
Machine learning/ Deep learning /Artificial Intelligence
Deep bi-prediction blending. This paper presents a learning-based method to improve bi-prediction in video coding. In conventional video coding solutions, block-based motion compensation blocks from already decoded reference pictures stand out as the main tool used to predict the current frame. Especially, bi-predicted blocks, i.e. blocks that combine two different...
Representation of 3D scenes is gaining popularity in industry, notably for Virtual Reality, Augmented Reality, and 360° Video. The point cloud format is well suited for such representations. Indeed, point clouds can be created with a simple capture process and modest processing, enabling a real-time, end-to-end point cloud distribution chain....
This paper describes a light field scalable compression scheme based on the sparsity of the angular Fourier transform of the light field. A subset of sub-aperture images (or views) is compressed using HEVC as a base layer and transmitted to the decoder. An entire light field is reconstructed from this...