Video-Robin: Autoregressive Diffusion Planning for Intent-Grounded Video-to-Music Generation
Video-to-music (V2M) is the fundamental task of creating background music for an input video. Recent V2M models achieve audiovisual alignment by typically relying on visual conditioning alone and provide limited semantic and stylistic controllability to the end user. In this paper, we present Video-Robin, a novel text-conditioned video-to-music generation model that enables fast, high-quality, semantically aligned music generation for video content. To balance musical fidelity and semantic understanding, Video-Robin integrates autoregressive planning with diffusion-based synthesis. Specifically, an autoregressive module models global structure by semantically aligning visual and textual i...
| Authors | Vaibhavi Lokegaonkar, Aryan Vijay Bhosale, Vishnu Raj et al. |
|---|---|
| Primary category | cs.SD |
| Published | 19 April 2026 |
| Last updated at source | 22 April 2026 |
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