Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …

In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

Denoising diffusion probabilistic models are becoming the leading generative modeling
paradigm for many important data modalities. Being the most prevalent in the computer …

Diffusion models currently achieve state-of-the-art performance for both conditional and
unconditional image generation. However, so far, image diffusion models do not support …

Controllable layout generation aims at synthesizing plausible arrangement of element
bounding boxes with optional constraints, such as type or position of a specific element. In …

Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …

Diffusion models have emerged as powerful generative models in the text-to-image domain.
This paper studies their application as observation-to-action models for imitating human …

This work is an update of my previous paper on the same topic published a few years ago
(Borji, 2019). With the dramatic progress in generative modeling, a suite of new quantitative …

Training generative models, such as GANs, on a target domain containing limited examples
(eg, 10) can easily result in overfitting. In this work, we seek to utilize a large source domain …

This explainer document aims to provide an overview of the current state of the rapidly
expanding work on synthetic data technologies, with a particular focus on privacy. The …