English

Secure & Personalized Music-to-Video Generation via CHARCHA

Artificial Intelligence 2025-02-06 v1 Computer Vision and Pattern Recognition Human-Computer Interaction Multimedia

Abstract

Music is a deeply personal experience and our aim is to enhance this with a fully-automated pipeline for personalized music video generation. Our work allows listeners to not just be consumers but co-creators in the music video generation process by creating personalized, consistent and context-driven visuals based on lyrics, rhythm and emotion in the music. The pipeline combines multimodal translation and generation techniques and utilizes low-rank adaptation on listeners' images to create immersive music videos that reflect both the music and the individual. To ensure the ethical use of users' identity, we also introduce CHARCHA (patent pending), a facial identity verification protocol that protects people against unauthorized use of their face while at the same time collecting authorized images from users for personalizing their videos. This paper thus provides a secure and innovative framework for creating deeply personalized music videos.

Keywords

Cite

@article{arxiv.2502.02610,
  title  = {Secure & Personalized Music-to-Video Generation via CHARCHA},
  author = {Mehul Agarwal and Gauri Agarwal and Santiago Benoit and Andrew Lippman and Jean Oh},
  journal= {arXiv preprint arXiv:2502.02610},
  year   = {2025}
}

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NeurIPS 2024 Creative AI Track

R2 v1 2026-06-28T21:32:34.084Z