Continuous Conditional GAN (CcGAN)

If you use this code, please cite

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1. Datasets

RC-49 Dataset (h5 file)

https://1drv.ms/u/s!Arj2pETbYnWQr7MY2Pr5qipSUpZKEQ?e=k8HfB6

Download ‘RC-49_64x64.h5’ and put it in ‘./CcGAN/dataset/RC-49’

modified UTKFace Dataset (h5 file)

https://1drv.ms/u/s!Arj2pETbYnWQr7MW_sGY9tJC4G3eMw?e=gmTA0w

Download ‘UTKFace_64x64.h5’ and put it in ‘./CcGAN/dataset/UTKFace’

2. Sample Usage

2.1 Simulation (‘./CcGAN/Simulation’)

First, set the ROOT_PATH in the ‘run_train.sh’ to yours.

Then, run ‘run_train.sh’.

2.2 RC-49 (‘./CcGAN/RC-49’)

First, set the ROOT_PATH and DATA_PATH in the ‘run_train.sh’ to yours.

Then, run ‘run_train.sh’.

2.3 UTKFace (‘./CcGAN/UTKFace’)

First, set the ROOT_PATH and DATA_PATH in ‘run_train.sh’ to yours.

Then, run ‘run_train.sh’.

3. Some results

3.1 Simulation: Circular 2-D Gaussians

Training data

cGAN

HVDL

SVDL

3.2 RC-49

Visual Comparison

FID vs Angle

NIQE vs Angle

Diversity vs Angle

3.3 UTKFace

Visual Comparison

FID vs Angle

NIQE vs Angle

Diversity vs Angle