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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: mit
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+ datasets:
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+ - NumlockUknowSth/Cine250K
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+ language:
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+ - en
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+ base_model:
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+ - Wan-AI/Wan2.1-T2V-1.3B
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+ pipeline_tag: text-to-video
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+ tags:
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+ - multi-shot
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+ ---
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+
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+ <div align="center">
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+
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+ <h1>CineTrans: Learning to Generate Videos with Cinematic Transitions via Masked Diffusion Models</h1>
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+
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+ [![](https://img.shields.io/static/v1?label=CineTrans&message=Project&color=purple)](https://uknowsth.github.io/CineTrans/)   [![](https://img.shields.io/static/v1?label=Paper&message=Arxiv&color=red&logo=arxiv)](https://arxiv.org/abs/2508.11484)   [![](https://img.shields.io/static/v1?label=Code&message=Github&color=blue&logo=github)](https://github.com/Vchitect/CineTrans)   [![](https://img.shields.io/static/v1?label=Dataset&message=HuggingFace&color=yellow&logo=huggingface)](https://huggingface.co/datasets/NumlockUknowSth/Cine250K)   
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+
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+
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+ <p><a href="https://scholar.google.com/citations?hl=zh-CN&user=TbZZSVgAAAAJ">Xiaoxue Wu</a><sup>1,2*</sup>,
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+ <a href="https://scholar.google.com/citations?user=0gY2o7MAAAAJ&amp;hl=zh-CN" target="_blank">Bingjie Gao</a><sup>2,3</sup>,
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+ <a href="https://scholar.google.com.hk/citations?user=gFtI-8QAAAAJ&amp;hl=zh-CN">Yu Qiao</a><sup>2&dagger;</sup>,
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+ <a href="https://wyhsirius.github.io/">Yaohui Wang</a><sup>2&dagger;</sup>,
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+ <a href="https://scholar.google.com/citations?user=3fWSC8YAAAAJ">Xinyuan Chen</a><sup>2&dagger;</sup></p>
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+
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+
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+ <span class="author-block"><sup>1</sup>Fudan University</span>
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+ <span class="author-block"><sup>2</sup>Shanghai Artificial Intelligence Laboratory</span>
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+ <span class="author-block"><sup>3</sup>Shanghai Jiao Tong University</span>
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+
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+
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+ <span class="author-block"><sup>*</sup>Work done during internship at Shanghai AI Laboratory</span> <span class="author-block"><sup>&dagger;</sup>Corresponding author</span>
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+
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+ </div>
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+
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+ ## πŸ“₯ Installation
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+ 1. Clone the Repository
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+ ```
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+ git clone https://github.com/UknowSth/CineTrans.git
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+ cd CineTrans
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+ ```
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+ 2. Set up Environment
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+ ```
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+ conda create -n cinetrans python==3.11.9
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+ conda activate cinetrans
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+
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+ pip install torch==2.5.1 torchvision==0.20.1 --index-url https://download.pytorch.org/whl/cu118
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+ pip install -r requirements.txt
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+ ```
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+
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+ ## πŸ€— Checkpoint
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+
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+ ### CineTrans-DiT
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+ Download the weights of [Wan2.1-T2V-1.3B](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B/tree/main) and [lora weights](https://huggingface.co/NumlockUknowSth/CineTrans-DiT/tree/main). Place them as:
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+ ```
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+ Wan2.1-T2V-1.3B/ # original weights
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+ │── google/
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+ β”‚ └── umt5-xxl/
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+ │── config.json
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+ │── diffusion_pytorch_model.safetensors
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+ │── models_t5_umt5-xxl-enc-bf16.pth
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+ │── Wan2.1_VAE.pth
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+ ckpt/
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+ └── weights.pt # lora weights
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+ ```
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+
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+ For more inference details, please refer to our [GitHub repository](https://github.com/Vchitect/CineTrans).
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+
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+ ## πŸ“‘ BiTeX
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+ If you find [CineTrans](https://github.com/Vchitect/CineTrans.git) useful for your research and applications, please cite using this BibTeX:
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+ ```
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+ @misc{wu2025cinetranslearninggeneratevideos,
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+ title={CineTrans: Learning to Generate Videos with Cinematic Transitions via Masked Diffusion Models},
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+ author={Xiaoxue Wu and Bingjie Gao and Yu Qiao and Yaohui Wang and Xinyuan Chen},
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+ year={2025},
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+ eprint={2508.11484},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CV},
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+ url={https://arxiv.org/abs/2508.11484},
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+ }
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+ ```