Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

Generative Adversarial Networks (GANs) is a novel class of deep generative models that
has recently gained significant attention. GANs learn complex and high-dimensional …

The recent success of text-to-image synthesis has taken the world by storm and captured the
general public's imagination. From a technical standpoint, it also marked a drastic change in …

Recent text-to-video generation approaches rely on computationally heavy training and
require large-scale video datasets. In this paper, we introduce a new task, zero-shot text-to …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Despite the stunning ability to generate high-quality images by recent text-to-image models,
current approaches often struggle to effectively compose objects with different attributes and …

Text-to-image synthesis has recently seen significant progress thanks to large pretrained
language models, large-scale training data, and the introduction of scalable model families …

Abstract We present the Pathways [1] Autoregressive Text-to-Image (Parti) model, which
generates high-fidelity photorealistic images and supports content-rich synthesis involving …

Recent text-to-image diffusion models are able to generate convincing results of
unprecedented quality. However, it is nearly impossible to control the shapes of different …

We present the content deformation field (CoDeF) as a new type of video representation
which consists of a canonical content field aggregating the static contents in the entire video …