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PixelNN – Example-Based Image Synthesis

cs.cmu.edu

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Re: PixelNN – Example-Based Image Synthesis

#31

Post by throwaway613834 »

ACow_Adonis wrote: post #4
otp124 wrote: post #3

I used to roll my eyes at crime television shows, whenever they said "Enhance" for a low quality image. Now it seems the possibility of that becoming realistic are increasing with a steady clip, based on this paper and other enhancement techniques I've seen posted here.

Except, and this is really the fundamental catch, it's not so much "enhance" as it is "project a believable substitute/interpretation". You fundamentally can't get back information that has been destroyed/or never captured in the first place. What you can do is fill in the gaps/information with plausible values. I don't know whether this sounds like I'm splitting hairs, but it's really important that the general publ…

> I don't know whether this sounds like I'm splitting hairs

Somewhat no, but somewhat yes. Thing is, while there can be lots of input images that generate the same output, it could be that only one (or a handful) of them would occur in reality. If this happens to sometimes be the case, and if you could somehow guarantee this was the case in some particular scenario, it could very well make sense to admit it as evidence. Of course, the issue is that figuring this out may not be possible...

Re: PixelNN – Example-Based Image Synthesis

#32

Post by c12 »

otp124 wrote: post #3

I used to roll my eyes at crime television shows, whenever they said "Enhance" for a low quality image. Now it seems the possibility of that becoming realistic are increasing with a steady clip, based on this paper and other enhancement techniques I've seen posted here.

The low resolution to high resolution image synthesis reminds me of the unblur tool that Adobe demoed during Adobe MAX in 2011. Here is the relevant clip if you're interested https://www.youtube.com/watch?v=xxjiQoTp864

Re: PixelNN – Example-Based Image Synthesis

#33

Post by jlebrech »

otp124 wrote: post #3

I used to roll my eyes at crime television shows, whenever they said "Enhance" for a low quality image. Now it seems the possibility of that becoming realistic are increasing with a steady clip, based on this paper and other enhancement techniques I've seen posted here.

It can give possible matches, i don't think it would be admissible in court. they could still trick a confession out of someone using that image.

Re: PixelNN – Example-Based Image Synthesis

#34

Post by SeanDav »

avian wrote: post #25

I found the title somewhat misleading. I was expecting some clever application of the nearest-neighbor interpolation. But this seems to involve neural nets and appears far from "simple" to me (I'm not in the image processing field though).

Agree. This appears to be more a clever implementation of an algorithm generating "artistic" impressions. In some cases, creating artifacts which simply were not part of the original picture.

Re: PixelNN – Example-Based Image Synthesis

#35

Post by smallnamespace »

thaw13579 wrote: post #5
otp124 wrote: post #3

I used to roll my eyes at crime television shows, whenever they said "Enhance" for a low quality image. Now it seems the possibility of that becoming realistic are increasing with a steady clip, based on this paper and other enhancement techniques I've seen posted here.

Approaches like these are hallucinating the high resolution images though--not something that we'd ever want being used for police work. That said, I wonder if it would perform better than eyewitness testimony...

> hallucinating the high resolution images though

To play devil's advocate though, modern neuroscience and neuropsychology basically tells us that that our brains reconstruct and recreate our memories every time we try to remember them. Our memories are highly malleable and prone to false implantation... and yet witness testimony is still the gold standard in courts.

Re: PixelNN – Example-Based Image Synthesis

#36

Post by murkle »

scarface74 wrote: post #29
ACow_Adonis wrote: post #4

Earlier quoted context omitted.

Except, and this is really the fundamental catch, it's not so much "enhance" as it is "project a believable substitute/interpretation". You fundamentally can't get back information that has been destroyed/or never captured in the first place. What you can do is fill in the gaps/information with plausible values. I don't know whether this sounds like I'm splitting hairs, but it's really important that the general publ…

What you can do though, in limited circumstances, is create a still picture with more detail from a lower quality video. https://photo.stackexchange.com/questions/17098/csi-image-re...

It's a well-known technique in astronomy, eg https://www.aanda.org/articles/aa/ps/2005/22/aa2320-04.ps.gz

Re: PixelNN – Example-Based Image Synthesis

#37

Post by nl »

To paraphrase Google Brain's Vincent Vanhoucke, this appears to be another example where using context prediction from neighboring values outperforms an autoencoder approach.

If 2017 was the year of GANs, 2018 will be the year context prediction.

Re: PixelNN – Example-Based Image Synthesis

#38

Post by [deleted] »

usrusr wrote: post #15
ACow_Adonis wrote: post #4

Earlier quoted context omitted.

Except, and this is really the fundamental catch, it's not so much "enhance" as it is "project a believable substitute/interpretation". You fundamentally can't get back information that has been destroyed/or never captured in the first place. What you can do is fill in the gaps/information with plausible values. I don't know whether this sounds like I'm splitting hairs, but it's really important that the general publ…

Yeah, replace the training set with cartoon characters and the crime show dialog goes like this: "Zoom! Enhance! Zoom! Enhance! Enhance! Oh my god it's full of Smurfs..."

[deleted]

Re: PixelNN – Example-Based Image Synthesis

#39

Post by KGIII »

jlebrech wrote: post #33
otp124 wrote: post #3

I used to roll my eyes at crime television shows, whenever they said "Enhance" for a low quality image. Now it seems the possibility of that becoming realistic are increasing with a steady clip, based on this paper and other enhancement techniques I've seen posted here.

It can give possible matches, i don't think it would be admissible in court. they could still trick a confession out of someone using that image.

It could also narrow down the list of suspects. From there, additional investigation can find more evidence. Having access to big data can help this.

Re: PixelNN – Example-Based Image Synthesis

#40

Post by IshKebab »

omtinez wrote: post #19
ZeroGravitas wrote: post #8

Earlier quoted context omitted.

To give specific examples from their test data, it added stubble to people who didn't have stubble, gave them a different shape of glasses, changed the color of cats, changed the color and brand of sport shoe. And even then, I'm a little suspicious of how close some of the images got to original without being given color information. It appears that info was either hidden in the original in a way not apparent to huma…

I haven't read the paper in full detail, but reading between the lines I'm guessing that there's a significant portion of manual processing and hand waving involved. From the abstract, emphasis mine: > the second stage uses a pixel-wise nearest neighbor method to map the smoothed output to multiple high-quality, high-frequency outputs in a controllable manner. My interpretation is that they select training data by ha…

Could be pretty great for police sketch artists. (Although pretty misleading for juries too.)
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