Training a convolution network for 4x upscaling of faces-only. Some progress but desaturation and dithering patterns...pic.twitter.com/S2CThu0w1Q
• goth gremlin • computational cognitive/neuroscience modeling • geek & techish Cypriot • plant aficionada • came up with #bropenscience • http://neuroplausible.com •
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Training a convolution network for 4x upscaling of faces-only. Some progress but desaturation and dithering patterns...pic.twitter.com/S2CThu0w1Q
Twitter's JPG ultra-compress the dithering patterns away, so why should I fix that ;-) Trains quite quickly, now may need to scale up!
Alex J. Champandard Retweeted Mario Klingemann
Simple color mapping could help with colors (thanks @quasimondo), but I should fix the loss function in first place:https://twitter.com/quasimondo/status/781470005150027776 …
Alex J. Champandard added,
Turns out I made mistakes in layers N-2 and N-1 (one parameter wrong), and they were throwing out all the hard work of previous 36 layers.
The two buggy layers still tried to fix problem (via dithering) and last layer also by trying to smooth things out, but too limited scope.
The latest setup of the convolution network has "decided" to generate overlapping circles around each original low-res pixels ;-)pic.twitter.com/JkWDFqlZkW
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