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README.md
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README.md
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# Image-to-Video
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首图
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## 模型介绍 (Introduction)
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介绍文字(强调两个特点:宽屏视频,无水印)
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炫酷示例
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## 快速使用 (Inference)
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### 依赖项 (Dependency)
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### 代码范例 (Code example)
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### 模型局限 (Limitation)
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## 训练数据介绍 (Training Data)
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## 相关论文以及引用信息 (Reference)
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```
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@inproceedings{luo2023videofusion,
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title={VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation},
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author={Luo, Zhengxiong and Chen, Dayou and Zhang, Yingya and Huang, Yan and Wang, Liang and Shen, Yujun and Zhao, Deli and Zhou, Jingren and Tan, Tieniu},
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booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
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year={2023}
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}
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@article{wang2023videocomposer,
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title={VideoComposer: Compositional Video Synthesis with Motion Controllability},
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author={Wang, Xiang and Yuan, Hangjie and Zhang, Shiwei and Chen, Dayou and Wang, Jiuniu and Zhang, Yingya and Shen, Yujun and Zhao, Deli and Zhou, Jingren},
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journal={arXiv preprint arXiv:2306.02018},
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year={2023}
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}
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```
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## 使用协议 (License Agreement)
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我们的代码和模型权重仅可用于个人/学术研究,暂不支持商用。
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## 联系我们 (Contact Us)
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如果你想联系我们的算法/产品同学, 或者想加入我们的算法团队(实习/正式), 欢迎发邮件至: <yingya.zyy@alibaba-inc.com>。
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configuration.json
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configuration.json
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{
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"framework": "pytorch",
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"task": "image-to-video-task",
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"model": {
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"type": "image-to-video-model",
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"model_args": {
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"ckpt_clip": "open_clip_pytorch_model.bin",
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"ckpt_unet": "img2video_ldm_0779000.pth",
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"ckpt_autoencoder": "v2-1_512-ema-pruned.ckpt",
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"seed": 666
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},
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"model_cfg": {
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}
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},
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"pipeline": {
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"type": "image-to-video-task-pipeline"
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}
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}
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BIN
img2video_ldm_0779000.pth
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img2video_ldm_0779000.pth
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open_clip_pytorch_model.bin
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open_clip_pytorch_model.bin
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v2-1_512-ema-pruned.ckpt
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v2-1_512-ema-pruned.ckpt
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