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For your eyes only: improving Netflix video quality with neural networks

The Netflix TechBlog

Bampis , Li-Heng Chen and Zhi Li When you are binge-watching the latest season of Stranger Things or Ozark, we strive to deliver the best possible video quality to your eyes. To do so, we continuously push the boundaries of streaming video quality and leverage the best video technologies.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. We rolled out encoding innovations such as per-title and per-shot optimizations, which provided significant quality-of-experience (QoE) improvement to Netflix members. This introductory blog focuses on an overview of our journey.

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Improving our video encodes for legacy devices

The Netflix TechBlog

by Mariana Afonso , Anush Moorthy , Liwei Guo , Lishan Zhu , Anne Aaron Netflix has been one of the pioneers of streaming video-on-demand content?—?we we announced our intention to stream video over 13 years ago, in January 2007?—?and how long it takes for the video to start playing), rebuffer rates, etc.,

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Optimized shot-based encodes for 4K: Now streaming!

The Netflix TechBlog

Since then, we’ve developed algorithms such as per-title encode optimizations and per-shot dynamic optimization , but these innovations were not back-ported on these premium bitstreams. We’ve worked hard over the last year to leapfrog to our most advanced encoding innovations?—?shot-optimized 8, 10, 12 and 16 Mbps?—?regardless

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Scaling Media Machine Learning at Netflix

The Netflix TechBlog

In addition, we provide a unified library that enables ML practitioners to seamlessly access video, audio, image, and various text-based assets. Training Performance Media model training poses multiple system challenges in storage, network, and GPUs. Background Match Cutting is a video editing technique.

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Netflix Cloud Packaging in the Terabyte Era

The Netflix TechBlog

By Xiaomei Liu , Rosanna Lee , Cyril Concolato Introduction Behind the scenes of the beloved Netflix streaming service and content, there are many technology innovations in media processing. It is worth pointing out that cloud processing is always subject to variable network conditions.

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MezzFS?—?Mounting object storage in Netflix’s media processing platform

The Netflix TechBlog

It’s used extensively in our media processing platform, which includes services like Archer and runs features like video encoding and title image generation on tens of thousands of Amazon EC2 instances. We are constantly innovating on video encoding technology at Netflix, and we have a lot of content to encode.

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