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20162026
most citedProgressive Growing of GANs for Improved Quality, Stability, and Variation

1.5k citations · 8.4k across the 21 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

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★ 161 cited

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…

cs.CV2019★ 80 cited

Few-Shot Unsupervised Image-to-Image Translation

Ming-Yu Liu, Xun Huang, Arun Mallya +4

Unsupervised image-to-image translation methods learn to map images in a given class to an analogous image in a different class, drawing on unstructured (non-registered) datasets o…

stat.ML2019★ 296 cited

Improved Precision and Recall Metric for Assessing Generative Models

Tuomas Kynkäänniemi, Tero Karras, Samuli Laine +2

The ability to automatically estimate the quality and coverage of the samples produced by a generative model is a vital requirement for driving algorithm research. We present an ev…

cs.LG2019★ 34 cited

High-Quality Self-Supervised Deep Image Denoising

Samuli Laine, Tero Karras, Jaakko Lehtinen +1

We describe a novel method for training high-quality image denoising models based on unorganized collections of corrupted images. The training does not need access to clean referen…