collaborators

6 papers

cs.SD2026

MusicLayout: Explicit Structural Planning for Controllable Text-to-Music Generation

Shuyu Li, Kejun Zhang, Jiahe Lei +5

Text-to-music generation has advanced rapidly, but current systems still rely primarily on global text prompts, leaving the structural organization of generated music implicit and…

eess.AS2025

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…

cs.SD2025

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…

cs.AI2025

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…

eess.AS2025

Assessing Data Replication in Symbolic Music via Adapted Structural Similarity Index Measure

Shulei Ji, Zihao Wang, Le Ma +2

AI-generated music may inadvertently replicate samples from the training data, raising concerns of plagiarism. Similarity measures can quantify such replication, thereby offering s…

cs.SD2025

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…