I am using the UNIT architecture (GitHub - milesial/Pytorch-UNet: PyTorch implementation of the U-Net for image semantic segmentation with high quality images) as an encoder-decoder for 3 RGB output images. The issue is that the borders of the output images have color issues as can be seen in the attached image.
I am using a 6-channel input (two images concatenated together) to generate a 3-channel output.
Hello,
do you crop your images in any way?
I have not cropped the images, the norm for face images is that they are aligned so that face features can be correlated. I will try out random cropping and see how it affects the results. Thanks 
Pls let me know whether this solves the issue. Do you need to do image segmentation? If not or if you are open to different approaches, you can try this: StyleALAE. If you pick the right size of the latent space, you can rather easily do image segmentation, too. If you are keen, I can send my/our implementation of the above presented paper with a little add on so that the latent space is more disentangled.
Thanks @nwn
I’ll try out the method sometime this week. I’ll take a look at the paper and let you know if I can adapt the method for my gains.
Cheers
