INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
AI-ART is an advanced tool that offers a wide range of capabilities in the realm of artwork generation. By simply providing text input, users can effortlessly generate diverse forms of artwork, including drawings, paintings, sketches, and even replicate specific artist styles. Additionally, users have the ability to define the desired characteristics of the resulting image or video. This powerful tool can either create visuals that possess those specific attributes or generate entirely new compositions by manipulating and combining existing images.One of the notable features of AI-ART is its ability to mimic the distinct art styles of various artists or emulate specific types of artwork. By leveraging the provided text input, the tool can produce images and videos that closely resemble the desired artistic style or reflect a particular genre of art.The applications of this model are extensive. Firstly, it can be employed to create completely original images by utilizing the text prompts, which are processed into tokens using a text encoder. This process enables the tool to generate unique visuals based on the given input.Furthermore, AI-ART facilitates image inpainting and outpainting by allowing users to provide both a text prompt and a starting image or video. By incorporating these inputs, the tool can fill in missing parts of an image or extend the content beyond its original boundaries. This capability proves particularly useful when users want to enhance or modify existing visuals.Moreover, the tool can generate videos by producing a series of images for each frame, ensuring coherence and accuracy throughout the video sequence. It is worth noting that the computational requirements for this process are reasonable, as the majority of the processing occurs in the latent space. Additionally, a variational autoencoder is employed to finalize the resulting image by incorporating the information derived from the latent space.
Keywords:
AI-ART, latent space,Text encoder,Image variational auto encoder,pixel information creator , inpainting , outpainting
Cite Article:
"AiArt", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.b14-b19, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305103.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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