@inproceedings{7938b082458346e9917382e94720210a,
title = "Iterative Visual Interaction with Latent Diffusion Models",
abstract = "Image synthesis generative Artificial Intelligence has the potential to revolutionize many industries, from rapid prototyping of consumer goods{\textquoteright} design to creating works of art. However, the most widespread of these models come in the form of text-to-image models. Controlling their output is often a difficult and imprecise process; indeed, slightly different prompts can lead to significantly different outcomes. Therefore, we develop a novel way to interact with generative AI that mimics the way in which humans naturally create works of art and design. We achieve this more granular and intuitive interaction method by exploiting the latent space of Latent Diffusion Models to generate image variations.",
keywords = "Generative AI, Human Centered AI, Latent Diffusion Models, Latent Space",
author = "Luca Sacchetto and Stefan R{\"o}hrl and Klaus Diepold",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 5th International Conference on Artificial Intelligence in HCI, AI-HCI 2024, held as part of the 26th HCI International Conference, HCII 2024 ; Conference date: 29-06-2024 Through 04-07-2024",
year = "2024",
doi = "10.1007/978-3-031-60606-9_24",
language = "English",
isbn = "9783031606052",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "411--421",
editor = "Helmut Degen and Stavroula Ntoa",
booktitle = "Artificial Intelligence in HCI - 5th International Conference, AI-HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Proceedings",
}