Text-to-image synthesis has recently seen significant progress thanks to...
Large-scale diffusion-based generative models have led to breakthroughs ...
Time-lapse image sequences offer visually compelling insights into dynam...
We present a video generation model that accurately reproduces object mo...
We argue that the theory and practice of diffusion-based generative mode...
Fréchet Inception Distance (FID) is a metric for quantifying the distanc...
We observe that despite their hierarchical convolutional nature, the
syn...
We present a modular differentiable renderer design that yields performa...
Training generative adversarial networks (GAN) using too little data
typ...
The style-based GAN architecture (StyleGAN) yields state-of-the-art resu...
Consistency regularization describes a class of approaches that have yie...
Unsupervised image-to-image translation methods learn to map images in a...
The ability to evaluate the performance of a computational model is a vi...
We describe techniques for training high-quality image denoising models ...
We propose an alternative generator architecture for generative adversar...
We apply basic statistical reasoning to signal reconstruction by machine...
We describe a new training methodology for generative adversarial networ...
We propose a new formulation for pruning convolutional kernels in neural...
In this paper, we present a simple and efficient method for training dee...
We present a real-time deep learning framework for video-based facial
pe...