PyTorch implementation of EigenGAN

Last update: Nov 12, 2022

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Overview

PyTorch Implementation of EigenGAN

Train

python train.py [image_folder_path] --name [experiment name]

Test

python test.py [ckpt path] --traverse

FFHQ

[ckpt]

samples (no truncation)

Learned subspace: L0 D1

Learned subspace: L1 D2

Anime

[ckpt]

samples (no truncation)

Learned subspace: L0 D5

Learned subspace: L1 D2

Note

Default training configurations are different from the original implementation

Tested on python 3.8 + torch 1.8.1

Issue

Some of the subspace layers seem to collapse (does not contribute to the output) as the training proceeds and FID gets better.

Owner

GitHub Repository

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