1.5k citations · 5.6k across the 20 of their papers we have counts for
3 papers · 1 filter
Modular Primitives for High-Performance Differentiable Rendering
Samuli Laine, Janne Hellsten, Tero Karras +3
We present a modular differentiable renderer design that yields performance superior to previous methods by leveraging existing, highly optimized hardware graphics pipelines. Our d…
Training Generative Adversarial Networks with Limited Data
Tero Karras, Miika Aittala, Janne Hellsten +3
Training generative adversarial networks (GAN) using too little data typically leads to discriminator overfitting, causing training to diverge. We propose an adaptive discriminator…
GANSpace: Discovering Interpretable GAN Controls
Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen +1
This paper describes a simple technique to analyze Generative Adversarial Networks (GANs) and create interpretable controls for image synthesis, such as change of viewpoint, aging,…