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> The generation network is therefore an approximate renderer that is learned from data. > https://www.youtube.com/watch?v=G-kWNQJ4idw&feature=youtu.be https:/
by tomxor 8y ago
> The generation network is therefore an approximate renderer that is learned from data.
> https://www.youtube.com/watch?v=G-kWNQJ4idw&feature=youtu.be https://www.youtube.com/watch?v=G-kWNQJ4idw&feature=youtu.be
I wonder if this is efficient... I know this isn't the researchers intended application, but the path tracer in me wants to see how far this can be pushed for real time rendering. I welcome the more interesting artefacts that a NN might produce (i'm talking about pigsnails [1] of course :D)
full circle: GPU GLSL for graphics -> GPU cuda/opencl for NN -> GPU cuda/opencl for NN graphics
[1] https://www.newscientist.com/article/dn27755-artificial-brain-turns-clouds-into-psychedelic-pig-snails/ https://www.newscientist.com/article/dn27755-artificial-brai...
- 21 8y agoThis is also very likely to be useful for video compression.
- halflings 8y agoDisney actually does a lot of research combining the world of graphics with deep learning. Some examples that you might appreciate (from the excellent channel "Two Minute Papers"): . "Disney's AI Learns To Render Clouds" [0] . "AI Learns Noise Filtering For Photorealistic Videos" [1] [0] https://www.youtube.com/watch?v=7wt-9fjPDjQ https://www.youtube.com/watch?v=7wt-9fjPDjQ [1] https://www.youtube.com/watch?v=YjjTPV2pXY0 https://www.youtube.com/watch?v=YjjTPV2pXY0
- tomxor 8y agoThanks! that is really some awesome stuff. It's even simpler in concept than this.