Innovative AI Solutions for Multi-Modal Content Generation
To overcome contemporary constraints in the field of AI-driven art generation, the AI ImageGen project offers a robust, intuitive framework for creating images utilizing different AI models. Utilizing a variety of cutting-edge models integrated through the Hugging Face API, this web application enables users to generate distinctive, high-quality photos by entering bespoke text prompts. AI ImageGen, which is built with React for the frontend and Node.js for the backend, provides a smooth user experience with a simplified UI thanks to Ant Design. In addition to creating photographs, users may efficiently manage their outputs by viewing, downloading, and deleting their creations. AI methods for creating images have historically advanced quickly, but many platforms still only provide a limited amount of customisation and model selection flexibility.By letting users select from a variety of models, AI ImageGen closes this gap and promotes output diversity and creativity. In order to facilitate the creation of AI-based art by a wider audience, this project also attempts to enhance the general usability of AI tools for nontechnical users. With its adaptable, multi-model methodology and emphasis on a seamless user experience, AI ImageGen is a cutting-edge solution in the rapidly expanding field of AI art generating.
Authors
- Anantha Murthy (ORCID: https://orcid.org/0000-0002-9009-7541)
- Rohan D’Souza (ORCID: https://orcid.org/0000-0002-4049-2017)
- G M Harshitha
- D. Vijay Praveen
- Keerthi Shetty
- Pruthvi Surender Borkar
Institutions
- National Institute of Technology Nagaland (IN)
Publication Details
- Published
- 2025-02-06
- DOI
- https://doi.org/10.1109/aide64228.2025.10987412
- Primary Topic
- Semantic Web and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00