Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design
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arXiv
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| Format: | Preprint |
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2024
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| author | Choi, Joong Ho Choi, Geonyeong Han, Ji-Eun Yang, Wonjin Cheng, Zhi-Qi |
| author_facet | Choi, Joong Ho Choi, Geonyeong Han, Ji-Eun Yang, Wonjin Cheng, Zhi-Qi |
| contents | In today's music industry, album cover design is as crucial as the music itself, reflecting the artist's vision and brand. However, many AI-driven album cover services require subscriptions or technical expertise, limiting accessibility. To address these challenges, we developed Music2P, an open-source, multi-modal AI-driven tool that streamlines album cover creation, making it efficient, accessible, and cost-effective through Ngrok. Music2P automates the design process using techniques such as Bootstrapping Language Image Pre-training (BLIP), music-to-text conversion (LP-music-caps), image segmentation (LoRA), and album cover and QR code generation (ControlNet). This paper demonstrates the Music2P interface, details our application of these technologies, and outlines future improvements. Our ultimate goal is to provide a tool that empowers musicians and producers, especially those with limited resources or expertise, to create compelling album covers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_01651 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design Choi, Joong Ho Choi, Geonyeong Han, Ji-Eun Yang, Wonjin Cheng, Zhi-Qi Multimedia Artificial Intelligence Human-Computer Interaction H.5.1; H.5.5 In today's music industry, album cover design is as crucial as the music itself, reflecting the artist's vision and brand. However, many AI-driven album cover services require subscriptions or technical expertise, limiting accessibility. To address these challenges, we developed Music2P, an open-source, multi-modal AI-driven tool that streamlines album cover creation, making it efficient, accessible, and cost-effective through Ngrok. Music2P automates the design process using techniques such as Bootstrapping Language Image Pre-training (BLIP), music-to-text conversion (LP-music-caps), image segmentation (LoRA), and album cover and QR code generation (ControlNet). This paper demonstrates the Music2P interface, details our application of these technologies, and outlines future improvements. Our ultimate goal is to provide a tool that empowers musicians and producers, especially those with limited resources or expertise, to create compelling album covers. |
| title | Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design |
| topic | Multimedia Artificial Intelligence Human-Computer Interaction H.5.1; H.5.5 |
| url | https://arxiv.org/abs/2408.01651 |