

Muvi
Overview :
MuVi is an innovative framework that analyzes video content to extract contextually and temporally relevant features, generating music that aligns with the mood, theme, rhythm, and tempo of the video. This framework implements a comparative music-visual pre-training scheme to ensure the periodic synchronization of musical phrases, and showcases the capabilities of a flow-matching-based music generator with contextual learning, allowing for control over the style and type of generated music. MuVi demonstrates superior performance in audio quality and temporal synchronization, providing new solutions for the integration of audio and video content and enhancing immersive experiences.
Target Users :
MuVi's target audience includes music producers, video editors, game developers, and professionals who need to generate music that matches video content. It is particularly suitable for users seeking to enhance the immersive experience and emotional expression of their videos, as it can create music that is semantically aligned with and rhythmically synchronized to the video content.
Use Cases
Generate background music for anime/cartoon videos to enhance viewing experience.
Create scores for silent films to recreate the emotional depth of classic cinema.
Produce dynamic music for game CGI videos to elevate immersive gameplay.
Generate tailored music for YouTube videos, comedy compilations, or meme videos to increase entertainment value.
Features
Video content analysis: Extract contextual features related to the video content using specially designed visual adapters.
Music generation: Create music that matches the mood, theme, rhythm, and tempo of the video.
Comparative music-visual pre-training: Ensure the periodic synchronization of musical phrases.
Contextual learning capability: Control the style and type of generated music.
Experimental results: Showcase superior performance in audio quality and temporal synchronization.
Multi-style music generation: Provide music clips in various styles as prompts, demonstrating MuVi's contextual learning capabilities.
Visual adapter attention visualization: Display the attention distribution of the visual adapter, reflecting the relevance of the generated music.
Comparison with baselines and real music: Highlight MuVi's advantages compared to baselines like M2UGen.
How to Use
1. Visit MuVi's official website or GitHub page.
2. Read the documentation to understand how MuVi works and its features.
3. Download and install the necessary software and dependencies.
4. Prepare the video content, ensuring that the video format is compatible with MuVi.
5. Use the tools and interfaces provided by MuVi to upload the video and set the music generation parameters.
6. Start the music generation process and wait for MuVi to analyze the video content and generate music.
7. Preview the generated music and its matching effect with the video, and adjust parameters as needed.
8. Export the generated music and video for personal or commercial projects.
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