research
∙
01/23/2023
StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis
Text-to-image synthesis has recently seen significant progress thanks to...
share
research
∙
11/02/2022
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
Large-scale diffusion-based generative models have led to breakthroughs ...
research
∙
07/04/2022
Disentangling Random and Cyclic Effects in Time-Lapse Sequences
Time-lapse image sequences offer visually compelling insights into dynam...
research
∙
06/07/2022
Generating Long Videos of Dynamic Scenes
We present a video generation model that accurately reproduces object mo...
research
∙
06/01/2022
Elucidating the Design Space of Diffusion-Based Generative Models
We argue that the theory and practice of diffusion-based generative mode...
research
∙
03/11/2022
The Role of ImageNet Classes in Fréchet Inception Distance
Fréchet Inception Distance (FID) is a metric for quantifying the distanc...
research
∙
06/23/2021
Alias-Free Generative Adversarial Networks
We observe that despite their hierarchical convolutional nature, the syn...
research
∙
11/06/2020
Modular Primitives for High-Performance Differentiable Rendering
We present a modular differentiable renderer design that yields performa...
research
∙
06/11/2020
Training Generative Adversarial Networks with Limited Data
Training generative adversarial networks (GAN) using too little data typ...
research
∙
12/03/2019
Analyzing and Improving the Image Quality of StyleGAN
The style-based GAN architecture (StyleGAN) yields state-of-the-art resu...
research
∙
06/05/2019
Consistency regularization and CutMix for semi-supervised semantic segmentation
Consistency regularization describes a class of approaches that have yie...
research
∙
05/05/2019
Few-Shot Unsupervised Image-to-Image Translation
Unsupervised image-to-image translation methods learn to map images in a...
research
∙
04/15/2019
Improved Precision and Recall Metric for Assessing Generative Models
The ability to evaluate the performance of a computational model is a vi...
research
∙
01/29/2019
Self-Supervised Deep Image Denoising
We describe techniques for training high-quality image denoising models ...
research
∙
12/12/2018
A Style-Based Generator Architecture for Generative Adversarial Networks
We propose an alternative generator architecture for generative adversar...
research
∙
03/12/2018
Noise2Noise: Learning Image Restoration without Clean Data
We apply basic statistical reasoning to signal reconstruction by machine...
research
∙
10/27/2017
Progressive Growing of GANs for Improved Quality, Stability, and Variation
We describe a new training methodology for generative adversarial networ...
research
∙
11/19/2016
Pruning Convolutional Neural Networks for Resource Efficient Inference
We propose a new formulation for pruning convolutional kernels in neural...
research
∙
10/07/2016
Temporal Ensembling for Semi-Supervised Learning
In this paper, we present a simple and efficient method for training dee...
research
∙
09/21/2016
