InfoGAN
InfoGAN Architecture
Tensorlayer implementation of InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets.
Results
MNIST
Manipulating the First Continuous Latent Code
Changing will rotate the digits:
Manipulating the Second Continuous Latent Code
Changing will change the width of the digits:
Manipulating the Discrete Latent Code (Categorical)
Changing will change the type of digits:
Random Generation and Loss Plot
G_loss increases steadily after a sufficient number of iterations, showing the discriminator is getting stronger and stronger and indicating the end of training.
CelebA
Manipulating Discrete Latent Code
Azimuth (pose):
Presence or absence of glasses:
Hair color:
Hair quantity:
Lighting:
Faces
Loss Plot
Azimuth
Random Generation
Chairs
Rotation
Run
MNIST
- Start training using
python train.py
; this will automatically download the dataset. - To see the results, execute
python test.py
and input the number of your saved model.
CelebA
- Set your image folder in
config.py
. - Some links for the datasets:
- Start training.
python train.py
Faces
- Set your data folder in
config.py
. - A link for BFM 2009:
- Basel Face Model. This should be downloaded before generating data.
- Data is generated using the code in
data_generator
. Callgen_data
in MATLAB.
- Start training using
python train.py
. - To see the results, execute
python test.py
and input the number of your saved model.
Chairs
- Set your image folder in
data.py
. - Some links for the datasets:
- Start training.
python train.py
References
- InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
- Large-scale CelebFaces Attributes (CelebA) Dataset
- THE MNIST DATABASE of handwritten digits
- Seeing 3D chairs: exemplar part-based 2D-3D alignment using a large dataset of CAD models
Authors
- 李舒辰 (@lisc55): The experiment on CelebA.
- 王畅 (@wangchang327): The experiment on MNIST.
- 竺沈涵 (@zshCuanNi): The experiment on Faces. Finished by 王畅 (@wangchang327).
- 岳鹏云 (@hswd40): The experiment on Chairs.