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  ## Overview
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  FETV consist of a diverse set of text prompts, categorized based on three orthogonal aspects: major content, attribute control, and prompt complexity.
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- ![](./categorization.png)
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  ## Dataset Structure
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  ### Data Instances
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  }
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  ```
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  ### Data Fields
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- * "video_id" is the video identifier in the original dataset where the prompt comes from.
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- * "prompt" is the text prompt for text-to-video generation.
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- * "major content", "attribute control" and "prompt complexity" are the three orthogonal aspects for categorization.
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- * "source" denotes the original dataset where the prompt comes from, which can be "WebVid", "MSRVTT" or "ours".
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- * "video_url" is the url link of the reference video.
 
 
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  ### Dataset Statistics
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  FETV contains 619 text prompts. The data distributions over different categories are as follows (the numbers over categories do not sum up to 619 because a data instance can belong to multiple categories)
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- ![](./content_attribute_statistics.png)
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- ![](./complexity_statistics.png)
 
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  ## Overview
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  FETV consist of a diverse set of text prompts, categorized based on three orthogonal aspects: major content, attribute control, and prompt complexity.
 
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  ## Dataset Structure
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  ### Data Instances
 
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  }
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  ```
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  ### Data Fields
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+ * "video_id": The video identifier in the original dataset where the prompt comes from.
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+ * "prompt": The text prompt for text-to-video generation.
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+ * "major content": The major content described in the prompt.
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+ * "attribute control": The attribute that the prompt aims to control.
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+ * "prompt complexity": The complexity of the prompt.
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+ * "source": The original dataset where the prompt comes from, which can be "WebVid", "MSRVTT" or "ours".
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+ * "video_url": The url link of the reference video.
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  ### Dataset Statistics
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  FETV contains 619 text prompts. The data distributions over different categories are as follows (the numbers over categories do not sum up to 619 because a data instance can belong to multiple categories)