GitHub - NVlabs/stylegan2-ada-pytorch: StyleGAN2-ADA - Official PyTorch implementation
Training Generative Adversarial Networks with Limited Data Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila https://arxiv.org/abs/2006.06676 Abstract: Training generative adversarial networks (GAN) using too little data typically leads to discriminator overfitting, causing training to diverge. We propose an adaptive discriminator augmentation mechanism that sign
GitHub - NVlabs/stylegan2-ada: StyleGAN2 with adaptive discriminator augmentation (ADA) - Official TensorFlow implementation
Training Generative Adversarial Networks with Limited Data Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila https://arxiv.org/abs/2006.06676 Abstract: Training generative adversarial networks (GAN) using too little data typically leads to discriminator overfitting, causing training to diverge. We propose an adaptive discriminator augmentation mechanism that sign
GitHub - NVlabs/stylegan: StyleGAN - Official TensorFlow Implementation
Picture: These people are not real – they were produced by our generator that allows control over different aspects of the image. This repository contains the official TensorFlow implementation of the following paper: A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras (NVIDIA), Samuli Laine (NVIDIA), Timo Aila (NVIDIA) https://arxiv.org/abs/1812.04948 Abstract: We
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