
AVA: The Art and Science of Image Discovery at Netflix - trueduke
https://medium.com/netflix-techblog/ava-the-art-and-science-of-image-discovery-at-netflix-a442f163af6
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bwang29
I see one potential downside of this, as a Netflix subscriber I do find the
frequent shuffle and changes of cover art confusing sometimes as it makes you
feel there is a new film coming out but in fact you've already watched it.

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dtien
Actually, this might be one of the intended effects of this feature. What
better way to make it appear their catalog is wider and ever-changing then to
cycle through these static stills every so often. It may not be the most user
friendly design pattern to 'trick' your user into thinking there's a bigger
catalog, but I can understand the desire for it from their perspective.

And to be perfectly honest, sometimes those changing stills have actually made
me watch a movie that I had previously glossed over because the image wasn't
as interesting. So from personal experience I can say their primary intent was
reached w/ the periodic cycling of stills.

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aub3bhat
You can setup AVA style video processing pipeline using my project
[https://www.deepvideoanalytics.com/](https://www.deepvideoanalytics.com/)

It comes built in with face detection/recognition, object detection, OCR, Open
Images tagger etc.

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rememberlenny
This is an incredible product.

I have come across the github repo's authors work a number of times now, and I
am continually impressed by the quality of documentation, examples, and
immediately usable code.

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nmstoker
Maybe they're not telling about some of the detail (and they've clearly given
it plenty of thought!) but it seems wasteful to fully process all frames when
in several cases many of them will never be selected. eg if it fails due to
poor Visual Metadata (such as strong motion blur or very low brightness) you'd
want to abandon all frames like that before running the other processing.

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mkl
They probably do, for efficiency. You have to process a frame to some extent
to detect motion blur or darkness (how else could you possibly know?), but
that doesn't mean you can't abort the processing as soon as you detect the
frame is totally unsuitable. I expect whole groups of frames may be able to be
discarded more-or-less together, e.g. a dark key frame followed by frames with
minimal difference, or where the video encoding's motion estimation says
there's a lot moving.

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invalidusernam3
I love this niche type of project, sounds like it would be such a fun project
to work on.

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m3kw9
Why don’t they Kaggle it?

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tedsanders
Netflix cancelled its second million-dollar Netflix Prize in 2010 due to
privacy lawsuits. Netflix has not outsourced its data science since.

[https://www.wired.com/2010/03/netflix-cancels-
contest/](https://www.wired.com/2010/03/netflix-cancels-contest/)

