Machine Learning Coffee seminar: "Progressive Growing of GANs for Improved Quality, Stability, and Variation"

Helsinki region machine learning researchers will start our week by an exciting machine learning talk. The aim is to gather people from different fields of science with interest in machine learning. Porridge and coffee is served at 9:00 and the talk will begin at 9:15.
CelebA dataset, NVIDIA

Progressive Growing of GANs for Improved Quality, Stability, and Variation

Tero Karras

Research Scientist, NVIDIA

We describe a new training methodology for generative adversarial networks. The key idea is to grow both the generator and discriminator progressively: starting from a low resolution, we add new layers that model increasingly fine details as training progresses. This both speeds the training up and greatly stabilizes it, allowing us to produce images of unprecedented quality, e.g., CelebA images at 1024^2. We also propose a simple way to increase the variation in generated images, and achieve a record inception score of 8.80 in unsupervised CIFAR10. Additionally, we describe several implementation details that are important for discouraging unhealthy competition between the generator and discriminator. Finally, we suggest a new metric for evaluating GAN results, both in terms of image quality and variation. As an additional contribution, we construct a higher-quality version of the CelebA dataset.

Tero Karras, Timo Aila, Samuli Laine, Jaakko Lehtinen, ICLR 2018

Please spread the news and join us for our weekly habit of beginning the week by an interesting machine learning talk!

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