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README.md

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-license: mit
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+---
+license: mit
+---
+
+# Diff-V2M: A Hierarchical Conditional Diffusion Model with Explicit Rhythmic Modeling for Video-to-Music Generation
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+Here is the training checkpoints of **[Diff-V2M (AAAI'26)](https://arxiv.org/abs/2312.10307)**
+
+## Overview
+
+Diff-V2M is a hierarchical diffusion model with explicit rhythmic modeling and multi-view feature conditioning, achieving state-of-the-art results in video-to-music generation..
+<img src="model.png" width="770" height="500" alt="model"/>
+
+## Model Sources
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** https://github.com/Tayjsl97/Diff-V2M
+- **Demo:** [demo page](https://tayjsl97.github.io/Diff-V2M-Demo)
+
+## Citation
+If you use our models in your research, please cite it as follows:
+```bib
+@inproceedings{ji2026diff,
+  title={Diff-V2M: A Hierarchical Conditional Diffusion Model with Explicit Rhythmic Modeling for Video-to-Music Generation},
+  author={Ji, Shulei and Wang, Zihao and Yu, Jiaxing and Yang, Xiangyuan and Li, Shuyu and Wu, Songruoyao and Zhang, Kejun},
+  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
+  year={2026}
+}