Latest advancements in video streaming with AI
AI developments in video streaming using Super-resolution, Per-title encoding, P2P
super-resolution deep-learning computer-vision video-classification artificial-general-intelligence machine-learning article tutorial

85% of the data consumed over the internet is via videos. About 2.8 exabytes of data is transferred over the internet via streaming videos. This growth is driven by the advent of VOD platforms like Netflix, Video communication platforms like Zoom, Social platforms like Tiktok, esports, live streaming to name a few.

Covid19 pandemic has accelerated the video consumption and has been the driving force of companies moving from offline mode to online live mode. With this explosion of the video consumption on a day-to-day basis we need to be prepared for the upcoming demand.

In this article we will be discussing what are the latest advancements in video streaming technology and how can they help in improving the streaming experience.

Don't forget to tag @Anil-matcha in your comment, otherwise they may not be notified.

Authors original post
Co-Founder @ Vadoo backed by JioGenNext, Ef | Ex-Samsung | IIT Delhi | Author at Paperspace
Share this project
Similar projects
Deep Learning Based Super Resolution, Without Using a GAN
Techniques and training a deep learning model for image improvement, image restoration, inpainting and super resolution.
Deep Tutorials for PyTorch
This is a series of in-depth tutorials I'm writing for implementing cool deep learning models on your own with the amazing PyTorch library.
Super-resolution Variational Auto-Encoders
VAE with RealNVP prior and Super-Resolution VAE in PyTorch.
Deep Learning for Image Super-resolution: A Survey
This article aims to provide a comprehensive survey on recent advances of image super-resolution using deep learning approaches.