Reproduction of Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis

- 1 min

GitHub project page

Paper

Usage

import sle_gan

G = sle_gan.Generator(output_resolution=512)
G.load_weights("generator_weights.h5")

input_noise = sle_gan.create_input_noise(batch_size=1)
generated_images = G(input_noise)
generated_images = sle_gan.postprocess_images(generated_images, tf.uint8).numpy()

Generated Images

These are not cherry picked

generated images 1

generated images 2

generated images 3

Difficulties throughout reproduction

When I was reading the paper, and I started the implementation I felt that lot of small but important details are missing. You can guess some of that from previous experience but I would love to see a more detailed description on this subject for a 100% reproduction.

Some of these:

Gábor Vecsei

Gábor Vecsei

I love chocolate

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