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@@ -54,7 +54,7 @@ pretty_name: TIP-I2V
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  ---
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  # Summary
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- This is the dataset proposed in our paper [**TIP-I2V: A Million-Scale Real Prompt-Gallery Dataset for Image-to-Video Diffusion Models**](https://arxiv.org/abs/2411.xxxxx).
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  TIP-I2V is the first dataset comprising over 1.70 million unique user-provided text and image prompts. Besides the prompts, TIP-I2V also includes videos generated by five state-of-the-art image-to-video models (Pika, Stable Video Diffusion, Open-Sora, I2VGen-XL, and CogVideoX-5B). The TIP-I2V contributes to the development of better and safer image-to-video models.
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@@ -211,7 +211,7 @@ The prompts and videos in our TIP-I2V are licensed under the [CC BY-NC 4.0 licen
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  # Citation
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  ```
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  @article{wang2024tipi2v,
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- title={TIP-I2V: A Million-Scale Real Prompt-Gallery Dataset for Image-to-Video Diffusion Models},
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  author={Wang, Wenhao and Yang, Yi},
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  booktitle={arXiv preprint arXiv:2411.xxxxx},
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  year={2024}
 
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  ---
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  # Summary
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+ This is the dataset proposed in our paper [**TIP-I2V: A Million-Scale Real Text and Image Prompt Dataset for Image-to-Video Generation**](https://arxiv.org/abs/2411.xxxxx).
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  TIP-I2V is the first dataset comprising over 1.70 million unique user-provided text and image prompts. Besides the prompts, TIP-I2V also includes videos generated by five state-of-the-art image-to-video models (Pika, Stable Video Diffusion, Open-Sora, I2VGen-XL, and CogVideoX-5B). The TIP-I2V contributes to the development of better and safer image-to-video models.
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  # Citation
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  ```
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  @article{wang2024tipi2v,
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+ title={TIP-I2V: A Million-Scale Real Text and Image Prompt Dataset for Image-to-Video Generation},
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  author={Wang, Wenhao and Yang, Yi},
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  booktitle={arXiv preprint arXiv:2411.xxxxx},
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  year={2024}