kwotsin / mimicry

[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.

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SSGAN missed Self-Modulation Normalization?

shimopino opened this issue · comments

Hi! Thank you for creating this easy-to-use library!

I was using your implementation of SSGAN to reproduce the original paper https://arxiv.org/abs/1810.01365.

As I read the original paper, the highest performing model was the one that used Self-Modulation Normalization, not Batch Normalization like your GBlock https://github.com/kwotsin/mimicry/blob/master/torch_mimicry/modules/resblocks.py#L73.

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Do you have any plans to add Self-Modulation Normalization?

Hi @KeisukeShimokawa, yes indeed I mostly compared to the version without sBN to keep the design simple as sBN is a general architectural improvement, but indeed it will be an interesting addition to have. Since it's suitable for most unconditional GAN I think it should be a good addition. Will keep this issue open and update in the future!

Excellent! Thanks!