I enjoyed this paper (I share a discord with the author so I read it a bit earlier).
It's not entirely clear from the comparison numbers at the end, but I think the big argument here is efficiency for the amount of performance achieved. One can get lower FID numbers, but also with a ton of compute.
I can't really speak technically to it as I've not given it a super in depth look, but this seems like a nice set of motifs for going halfway between a standard attention network and a convnet in terms of compute cost (and maybe performance)?
The large-resolution scaling seems to be a strong suit as a result. :)
It's not entirely clear from the comparison numbers at the end, but I think the big argument here is efficiency for the amount of performance achieved. One can get lower FID numbers, but also with a ton of compute.
I can't really speak technically to it as I've not given it a super in depth look, but this seems like a nice set of motifs for going halfway between a standard attention network and a convnet in terms of compute cost (and maybe performance)?
The large-resolution scaling seems to be a strong suit as a result. :)