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new_name_who_dis_ t1_ispgfn7 wrote

I'm currently working on a similar problem and my current approach is to add some noise (but not a lot) on the image in domain A, and then denoise with network trained on generating images in domain B.

It's not perfect, but it works. I'd be interested to hear more discussion of this topic.

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cygn t1_isx84ko wrote

could you show some images please?

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new_name_who_dis_ t1_isy3qr2 wrote

It's proprietary data so I can't. If you have a public dataset (or I guess 2 for style/domain transfer), I could run my code on it and get back to you.

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cygn t1_it25agy wrote

you could use one of the datasets that are listed here: https://paperswithcode.com/task/domain-adaptation

Office-31 for example looks quite practical. It has product images from Amazon, DSLR and webcam images. The problems I'd like to solve are similar. Take good images of plants with diseases and adapt them to images taken from users with smartphones with lots of quality issues.

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