We present a diffusion-based model for 3D-aware generative novel view
sy...
Text-to-image synthesis has recently seen significant progress thanks to...
We propose a deep learning method for three-dimensional reconstruction i...
Large-scale diffusion-based generative models have led to breakthroughs ...
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...
Unsupervised generation of high-quality multi-view-consistent images and...
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...
Disentanglement learning is crucial for obtaining disentangled
represent...
The style-based GAN architecture (StyleGAN) yields state-of-the-art resu...
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 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...
We present a real-time deep learning framework for video-based facial
pe...