👍 On Mon, Apr 4, 2022 at 8:37 PM Marcus Daniels <[email protected]> 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 <[email protected]> > 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 <[email protected]> > wrote: > >> aaaaaaaaaaaaaaah! coool!! thanks! >> >> On Mon, Apr 4, 2022 at 5:30 PM Marcus Daniels <[email protected]> >> 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 <[email protected]> *On Behalf Of *Gillian >>> Densmore >>> *Sent:* Monday, April 4, 2022 3:25 PM >>> *To:* The Friday Morning Applied Complexity Coffee Group < >>> [email protected]> >>> *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? >>> >>> .-- .- -. - / .- -.-. - .. --- -. ..--.. / -.-. --- -. .--- ..- --. .- - >>> . >>> FRIAM Applied Complexity Group listserv >>> Zoom Fridays 9:30a-12p Mtn UTC-6 bit.ly/virtualfriam >>> un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com >>> FRIAM-COMIC http://friam-comic.blogspot.com/ >>> archives: >>> 5/2017 thru present https://redfish.com/pipermail/friam_redfish.com/ >>> 1/2003 thru 6/2021 http://friam.383.s1.nabble.com/ >>> >> > .-- .- -. - / .- -.-. - .. --- -. ..--.. / -.-. --- -. .--- ..- --. .- - . > FRIAM Applied Complexity Group listserv > Zoom Fridays 9:30a-12p Mtn UTC-6 bit.ly/virtualfriam > un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com > FRIAM-COMIC http://friam-comic.blogspot.com/ > archives: > 5/2017 thru present https://redfish.com/pipermail/friam_redfish.com/ > 1/2003 thru 6/2021 http://friam.383.s1.nabble.com/ > > > .-- .- -. - / .- -.-. - .. --- -. ..--.. / -.-. --- -. .--- ..- --. .- - . > FRIAM Applied Complexity Group listserv > Zoom Fridays 9:30a-12p Mtn UTC-6 bit.ly/virtualfriam > un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com > FRIAM-COMIC http://friam-comic.blogspot.com/ > archives: > 5/2017 thru present https://redfish.com/pipermail/friam_redfish.com/ > 1/2003 thru 6/2021 http://friam.383.s1.nabble.com/ >
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