1 citations · 2 across the 9 of their papers we have counts for
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Diff-V2M: A Hierarchical Conditional Diffusion Model with Explicit Rhythmic Modeling for Video-to-Music Generation
Shulei Ji, Zihao Wang, Jiaxing Yu +4
Video-to-music (V2M) generation aims to create music that aligns with visual content. However, two main challenges persist in existing methods: (1) the lack of explicit rhythm mode…
SSIMuse: Assessing Data Replication in Symbolic Music via an Adapted Structural Similarity Index Measure
Shulei Ji, Zihao Wang, Le Ma +2
AI-generated music may inadvertently replicate training samples and raise plagiarism concerns. Similarity measures can quantify such replication, thereby offering supervision and g…
Losing is for Cherishing: Data Valuation Based on Machine Unlearning and Shapley Value
Le Ma, Shirao Yang, Zihao Wang +4
The proliferation of large models has intensified the need for efficient data valuation methods to quantify the contribution of individual data providers. Traditional approaches, s…
A Survey on Music Generation from Single-Modal, Cross-Modal, and Multi-Modal Perspectives
Shuyu Li, Shulei Ji, Zihao Wang +3
Multi-modal music generation, using multiple modalities like text, images, and video alongside musical scores and audio as guidance, is an emerging research area with broad applica…
A Comprehensive Survey on Generative AI for Video-to-Music Generation
Shulei Ji, Songruoyao Wu, Zihao Wang +2
The burgeoning growth of video-to-music generation can be attributed to the ascendancy of multimodal generative models. However, there is a lack of literature that comprehensively…