activity
20182021
most citedAlias-Free Generative Adversarial Networks

853 citations · 871 across the 2 of their papers we have counts for

collaborators

10 papers

cs.CV2021853 cited

Alias-Free Generative Adversarial Networks

Tero Karras, Miika Aittala, Samuli Laine +4

We observe that despite their hierarchical convolutional nature, the synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unheal…

cs.GR202118 cited

Appearance-Driven Automatic 3D Model Simplification

Jon Hasselgren, Jacob Munkberg, Jaakko Lehtinen +2

We present a suite of techniques for jointly optimizing triangle meshes and shading models to match the appearance of reference scenes. This capability has a number of uses, includ…

cs.GR2020

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…

cs.CV2020

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…

cs.CV2019

Analyzing and Improving the Image Quality of StyleGAN

Tero Karras, Samuli Laine, Miika Aittala +3

The style-based GAN architecture (StyleGAN) yields state-of-the-art results in data-driven unconditional generative image modeling. We expose and analyze several of its characteris…

cs.CV2019

Semi-supervised semantic segmentation needs strong, varied perturbations

Geoff French, Samuli Laine, Timo Aila +2

Consistency regularization describes a class of approaches that have yielded ground breaking results in semi-supervised classification problems. Prior work has established the clus…