Live data from Hacker News

Photos from Crude Sketches: Nvidia's GauGAN Explained Visually

adamdking.com

1–10 of 27 posts

Re: Photos from Crude Sketches: Nvidia's GauGAN Explained Visually

#2
If you want to see the same thing done 18 years ago without new-age machine learning, read https://www.mrl.nyu.edu/projects/image-analogies/index.html IMO the most elegant vision/graphics algorithm ever written.

Specifically this is the "texture-by-numbers" application. Ex: https://www.mrl.nyu.edu/projects/image-analogies/potomac.htm...

Every single fancypants application of neural nets in graphics today is a retread of one of the applications of the Image Analogies algorithm.

Re: Photos from Crude Sketches: Nvidia's GauGAN Explained Visually

#3
post #2

If you want to see the same thing done 18 years ago without new-age machine learning, read https://www.mrl.nyu.edu/projects/image-analogies/index.html IMO the most elegant vision/graphics algorithm ever written. Specifically this is the "texture-by-numbers" application. Ex: https://www.mrl.nyu.edu/projects/image-analogies/potomac.htm... Every single fancypants application of neural nets in graphics today is a retread…

This is not same:

"we first label a photograph or painting by hand to indicate its component textures. We then give a new labeling, from which the analogies algorithm produces a new photograph"

DL approach generalizes over many images and can derive some some "idea" of how given class should look like (ie. a tree)

Re: Photos from Crude Sketches: Nvidia's GauGAN Explained Visually

#4
post #2

If you want to see the same thing done 18 years ago without new-age machine learning, read https://www.mrl.nyu.edu/projects/image-analogies/index.html IMO the most elegant vision/graphics algorithm ever written. Specifically this is the "texture-by-numbers" application. Ex: https://www.mrl.nyu.edu/projects/image-analogies/potomac.htm... Every single fancypants application of neural nets in graphics today is a retread…

Is it really the same thing? The method you cite is a type of style transfer. Input sharp focused image and you get a blurrier version out with the required style. You’re removing information with a particular type of convolution.

The nvidia version seems to inpaint new details into the user segmented areas, like a collage of sorts.

Re: Photos from Crude Sketches: Nvidia's GauGAN Explained Visually

#8
I find this ... disquieting. I think its fantastic but I also find something about the lack of uncanny valley troubling.

I should feel happier about it, but I can't stop feeling a bit odd that a sketch can go to photorealistic north of the bad so well now: I expected 5-10 more years for this.

Re: Photos from Crude Sketches: Nvidia's GauGAN Explained Visually

#9
post #8

I find this ... disquieting. I think its fantastic but I also find something about the lack of uncanny valley troubling. I should feel happier about it, but I can't stop feeling a bit odd that a sketch can go to photorealistic north of the bad so well now: I expected 5-10 more years for this.

I'm not sure that I agree, the only images on the linked page are pretty tiny thumbnails, and the poorly compressed video - where I can definitely see some artifacting already that doesn't seem to be caused by the video compression, there's no way to know if they actually did a good job from that.

Re: Photos from Crude Sketches: Nvidia's GauGAN Explained Visually

#10
Imagine the impact on moviemaking that this will have within just a few iterations of processing power. Thousands of hours of visual effect artist work in film and TV will soon be abstracted into some high-level commands, transformed by software into moving film. Very exciting.
Post reply on HN