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Can ELEGANT perform inter-class translation? #19

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imlixinyang opened this issue Dec 26, 2019 · 6 comments
Open

Can ELEGANT perform inter-class translation? #19

imlixinyang opened this issue Dec 26, 2019 · 6 comments

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@imlixinyang
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@imlixinyang
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Another question is that it is shown that ELEGANT can perform multi-label translation, but I wonder whether it is performed by two-step translation or a single step (exchange two codes in or not in the meantime)?

@Prinsphield
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Prinsphield commented Dec 26, 2019

I guess the question that you are asking is: can we swap the hairstyle of two images with bangs? I did not try that, but I think ELEGANT can do that.

It is done in a single step translation. We claim that ELEGANT can control multiple attributes simultaneously. See Fig. 9.

@imlixinyang
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Thank you for your reply, I'll have a try later.
It would be amazing if it works because these two tasks are not involved in the training.

@Jessicall
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I guess the question that you are asking is: can we swap the hairstyle of two images with bangs? I did not try that, but I think ELEGANT can do that.

It is done in a single step translation. We claim that ELEGANT can control multiple attributes simultaneously. See Fig. 9.

hello @Prinsphield About the second question, it means exchanging two attribute codes of two reference images with the code of input image in the meantime? I wonder how is this achieved? because the model is performed on a reference image and an input image.

@Prinsphield
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I guess the question that you are asking is: can we swap the hairstyle of two images with bangs? I did not try that, but I think ELEGANT can do that.
It is done in a single step translation. We claim that ELEGANT can control multiple attributes simultaneously. See Fig. 9.

hello @Prinsphield About the second question, it means exchanging two attribute codes of two reference images with the code of input image in the meantime? I wonder how is this achieved? because the model is performed on a reference image and an input image.

Hello @Jessicall, since different attribute codes are disentangled represented in the latent encodings, so we can exchange the encodings of the input and two reference images simultaneously. You may refer to the code for details.

@Jessicall
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Thanks for your reply!

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