3 ms·
The model has 18x512 parameters, and all 9000 parameters are 32-bit floats. Even assuming only 16 bits of randomness for each parameter (to keep them small eno
by lsb 7y ago
The model has 18x512 parameters, and all 9000 parameters are 32-bit floats.
Even assuming only 16 bits of randomness for each parameter (to keep them small enough, so you don't get too wild, because the center of 0 is a pretty homogenized face), 16^9000 is a lot of permuations of faces.
They will, of course, borrow from all of the 70k faces on Flickr that power StyleGAN, in varying degrees.
- steerablesafe 7y ago> Even assuming only 16 bits of randomness for each parameter Well, this is the question. How do you know that you can make that assumption? Also even though you have ~9000 parameters they could be highly dependent.
- jonplackett 7y agoCould it by chance recreate on an input image though? Is it not possible, or just incredibly unlikely? I also wonder how similar to an original person it needs to be before you would believe it's them anyway.
- deleted 7y ago[deleted]
- 6gvONxR4sf7o 7y agoYou could use this argument to say that GANs can't overfit if you provide them, say, 16 bits of randomness per parameter, which is patently not true.