Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design

Autor:	Choi, Joong Ho, Choi, Geonyeong, Han, Ji-Eun, Yang, Wonjin, Cheng, Zhi-Qi
Rok vydání:	2024
Předmět:	Computer Science - Multimedia Computer Science - Artificial Intelligence Computer Science - Human-Computer Interaction H.5.1 H.5.5
Druh dokumentu:	Working Paper
Popis:	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. Comment: Accepted at CIKM 2024 Demo Paper track. Project available at https://github.com/JC-78/Music2P
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2408.01651 Zobrazit plný text záznamu View this record from Arxiv