Tensorflow Inplementation for AACNN : Attribute Augmented Convolutional Neural Network for Face Hallucination (NTIRE2018)
Attribute Augmented Convolutional Neural Network for Face Hallucination
Cheng-Han Lee 1, Kaipeng Zhang 1, Hu-Cheng Lee 1, Chia-Wen Cheng 2, and Winston H. Hsu 1
1 National Taiwan University, 2 The University of Texas at Austin
IEEE Conference on Computer Vision and Pattern Recognition Workshop, (NTIRE 2018)
[Supplementary Material]
- The Installation completely the same as our dependencies. Make sure you have correctly installed before using our code.
- Download the aligned version of CelebA dataset for training and testing
- Preprocess the training face images to 112 X 96, including detection, alignment, etc. Here we strongly recommend MTCNN, which is an effective and efficient open-source tool for face detection and alignment.
- Put aligned images under "./data/CelebA"
- For L2 version : bash train.sh #GPU
- For L2 + GAN version : bash train_gan.sh #GPU
- bash test.sh #GPU
- For PSNR evaluation : run test_psnr.m on Matlab
- For SSIM evaluation : run test_ssim.m on Matlab
- Add auxilary classifier loss
- Replace BatchNorm in discriminator with SpectralNorm