<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Text-to-image generation is a rapidly growing field that aims to generate images from textual descriptions. This paper provides a comprehensive overview of the latest trends and developments, highlighting their importance and relevance in various domains, such as art, photography, marketing, and learning. The paper describes and compares various text-to-image models and discusses the challenges and limitations of this field. The findings of this paper demonstrate that recent advancements in deep learning and computer vision have led to significant progress in text-to-image models, enabling them to generate high-quality images from textual descriptions. However, challenges such as ensuring the legality and ethical implications of the final products generated by these models need to be addressed. This paper provides insights into these challenges and suggests future directions for this field. In addition, this study emphasises the need for a sustainability-oriented approach in the text-to-image domain. As text-to-image models advance, it is crucial to conscientiously assess their impact on ecological, cultural, and societal dimensions. Prioritising ethical model use while being mindful of their carbon footprint and potential effects on human creativity becomes crucial for sustainable progress.</p>
</abstract>

Text-to-image generation is a rapidly growing field that aims to generate images from textual descriptions. This paper provides a comprehensive overview of the latest trends and developments, highlighting their importance and relevance in various domains, such as art, photography, marketing, and learning. The paper describes and compares various text-to-image models and discusses the challenges and limitations of this field. The findings of this paper demonstrate that recent advancements in deep learning and computer vision have led to significant progress in text-to-image models, enabling them to generate high-quality images from textual descriptions. However, challenges such as ensuring the legality and ethical implications of the final products generated by these models need to be addressed. This paper provides insights into these challenges and suggests future directions for this field. In addition, this study emphasises the need for a sustainability-oriented approach in the text-to-image domain. As text-to-image models advance, it is crucial to conscientiously assess their impact on ecological, cultural, and societal dimensions. Prioritising ethical model use while being mindful of their carbon footprint and potential effects on human creativity becomes crucial for sustainable progress.

Trends and Challenges of Text-to-Image Generation: Sustainability Perspective

Croatian Regional Development Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Trends and Challenges of Text-to-Image Generation: Sustainability Perspective"}

Text-to-image generation is a rapidly growing field that aims to generate images from textual descriptions. This paper provides a comprehensive overview of the...

Trends and Challenges of Text-to-Image Generation: Sustainability Perspective

Pubblicato online: 19 dic 2023

Pagine: 56 - 77

Ricevuto: 17 feb 2023

Accettato: 29 ago 2023

DOI: https://doi.org/10.2478/crdj-2023-0004

Parole chiave
artificial intelligence, natural language processing, text-to-image generation, sustainability, ethical artificial intelligence

© 2023 Dora Ivezić et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Trends and Challenges of Text-to-Image Generation: Sustainability Perspective

Pubblicato online: 19 dic 2023

Pagine: 56 - 77

Ricevuto: 17 feb 2023

Accettato: 29 ago 2023

DOI: https://doi.org/10.2478/crdj-2023-0004

Parole chiaveartificial intelligence, natural language processing, text-to-image generation, sustainability, ethical artificial intelligence

© 2023 Dora Ivezić et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
artificial intelligence, natural language processing, text-to-image generation, sustainability, ethical artificial intelligence