How I wrote a script to generate faces by inverting Haar cascades with Python

Re:How I wrote a script to generate faces by inverting Haar ... by arimorcos on Tuesday January 19, 2016 @07:55AM (#10930362)

Generative adversarial networks can do this much much better. Check out this blog post:

http://www.foldl.me/2015/conditional-gans-face-generation/

and the corresponding paper:

http://www.foldl.me/uploads/2015/conditional-gans-face-gener...

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Re:How I wrote a script to generate faces by inverting Haar ... by kastnerkyle on Tuesday January 19, 2016 @08:53AM (#10930709)

If we really want to get into "what is better" - the state of the art has recently moved significantly past this (paper [1] and blog [2]) - not to mention the recent submissions to ICLR in this realm [3][4]. GAN training is very tricky to get working in practice, especially on new problems, though conditional GAN seems to be a bit more stable in learning than the unconditional relatives.

This blog deserves credit for thinking differently about a problem and getting something useful out of it.

I think the goal of this inversion was to inspect what the cascade is "looking at" in some sense - and for that this does a great job! Inverting a lossy classification feature is nearly always going to be worse than something designed from the ground up to be a generative model.

[1] http://arxiv.org/abs/1512.09300

[2] http://torch.ch/blog/2015/11/13/gan.html

[3] https://github.com/Newmu/dcgan_code

[4] http://arxiv.org/abs/1511.05644

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