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 …

Image diffusion models such as DALL-E 2, Imagen, and Stable Diffusion have attracted
significant attention due to their ability to generate high-quality synthetic images. In this work …

Generative adversarial networks (GANs) have drawn enormous attention due to their simple
yet effective training mechanism and superior image generation quality. With the ability to …

Recently video generation has achieved substantial progress with realistic results.
Nevertheless, existing AI-generated videos are usually very short clips (" shot-level'') …

We systematically study a wide variety of generative models spanning semantically-diverse
image datasets to understand and improve the feature extractors and metrics used to …

Particle-based deep generative models, such as gradient flows and score-based diffusion
models, have recently gained traction thanks to their striking performance. Their principle of …

Generative adversarial networks (GANs), a novel framework for training generative models
in an adversarial setup, have attracted significant attention in recent years. The two …

We aim for image-based novelty detection. Despite considerable progress, existing models
either fail or face dramatic drop under the so-called``near-distribution" setup, where the …

Since the introduction of deep learning, a wide scope of representation properties, such as
decorrelation, whitening, disentanglement, rank, isotropy, and mutual information, have …

This study explores the impact of generative artificial intelligence tools on critical thinking
and collaboration among university students, highlighting the importance of investigating …