[FRIAM] This is scary, and yet very cool...Ai neural networks making pictures, look really good

[Marcus Daniels]

Speaking of which,  https://openai.com/dall-e-2/

From: Friam <friam-bounces at redfish.com> On Behalf Of Gillian Densmore
Sent: Monday, April 4, 2022 10:01 PM
To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com>
Subject: Re: [FRIAM] This is scary, and yet very cool...Ai neural networks making pictures, look really good

👍

On Mon, Apr 4, 2022 at 8:37 PM Marcus Daniels <marcus at snoutfarm.com<mailto:marcus at snoutfarm.com>> wrote:
I am not a photographer but I have been startled by how recent iPhone photos sometimes look better than what I saw when I took it.   This article explains..

https://www.newyorker.com/culture/infinite-scroll/have-iphone-cameras-become-too-smart

Filmy-ness sounds like crude interpolation more than structure being imposed.

Suppose I had 1000 pictures of my dog in many lighting conditions and from different angles.  Using photogrammetry reconstruction techniques these could be used to prepare a 3-d textured model of her.   My iPhone could determine that the 1001st photo also included her.  It could then reference this model to enhance her image in the new context.   Maybe inferring the light sources and ray tracing her at the required orientation and scale, but at a resolution far beyond what was in the photo.  That would be more art than a photo, but who cares about the truth anymore?  Photos are to be staged!



On Apr 4, 2022, at 5:04 PM, Gillian Densmore <gil.densmore at gmail.com<mailto:gil.densmore at gmail.com>> wrote:

Is that also why some of the older software for upscaling tricks the new pictures have a  kind of saturated or  filmy thing over them? or is that just from the particular Neural Networks or Ai models used?  Still very impressive.

On Mon, Apr 4, 2022 at 5:40 PM Gillian Densmore <gil.densmore at gmail.com<mailto:gil.densmore at gmail.com>> wrote:
aaaaaaaaaaaaaaah! coool!! thanks!

On Mon, Apr 4, 2022 at 5:30 PM Marcus Daniels <marcus at snoutfarm.com<mailto:marcus at snoutfarm.com>> wrote:
The idea [1] is that they learn the distribution function of different kinds of distortion using a machine learning algorithm.
Then that algorithm can invert that distribution function.  Kind of like a lens can correct for nearsightedness.

[1] https://arxiv.org/pdf/2107.10833.pdf
From: Friam <friam-bounces at redfish.com<mailto:friam-bounces at redfish.com>> On Behalf Of Gillian Densmore
Sent: Monday, April 4, 2022 3:25 PM
To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com<mailto:friam at redfish.com>>
Subject: [FRIAM] This is scary, and yet very cool...Ai neural networks making pictures, look really good

https://github.com/xinntao/ESRGAN

Stumbled across this looking for a way to gently adjust some old pictures of mine without watermarks (gigapixel), photoshop wasn't cutting it  because not enough pixels or data in the originals.

I am beyond fascinated how do they do it? just guess based on colors and add more pixels with that color?

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