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View Code? Open in Web Editor NEWPytorch implemenation of Stochastic Multi-Label Image-to-image Translation (SMIT), ICCV Workshops 2019.
License: MIT License
Pytorch implemenation of Stochastic Multi-Label Image-to-image Translation (SMIT), ICCV Workshops 2019.
License: MIT License
Horovod support parallelization.
For example, input an image with bangs, can smit change the bangs style by random style and unchanged labels? I don't know if you have tried this.
Hi, thanks for your good job! I wanted to download the weight of Painter14 for test, however, I encountered 403 problem in your website. Can you provide a new address?
Resultados finales: Circulos verdes significan inicio y final de interpolación de estilos, respectivamente.
Estos resultados son SIN regularizar el estilo. Me di cuenta que simplemente inyectando ruido aleatorio genera mejores imágenes, que si reconstruyo el estilo. Y lo más raro es que no hace mode collapse, al menos no muy grave. Es decir, no necesitamos un "style encoder". Esto va en contra de lo que se dice que inyectar ruido aleatorio hace que la red lo ignore si no se regulariza.
I apply your code to celeba-hq, but found the loss of attention turn to 0 and so the networks do nothing. Why?
the d_cls is about 10 while g_cls go to 30 but networks seem to never optim this.
Another question is that why you set the parameter of DE fixed?
Deterministic flag ends in error due to the AdaIN_res = False
in the generator.py
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