FETV / README.md
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metadata
license: cc-by-4.0
task_categories:
  - text-to-video
language:
  - en

FETV

FETV is a benchmark for Fine-grained Evaluation of open-domain Text-to-Video generation

Overview

FETV consist of a diverse set of text prompts, categorized based on three orthogonal aspects: major content, attribute control, and prompt complexity.

Dataset Structure

Data Instances

All FETV data are all available in the file fetv_data.json. Each line is a data instance, which is formatted as:

{
  "video_id": 1006807024, 
  "prompt": "A mountain stream", 
  "major content": {
       "spatial": ["scenery & natural objects"], 
       "temporal": ["fluid motions"]
     }, 
  "attribute control": {
      "spatial": null, 
      "temporal": null
    }, 
  "prompt complexity": ["simple"], 
  "source": "WebVid", 
  "video_url": "https://ak.picdn.net/shutterstock/videos/1006807024/preview/stock-footage-a-mountain-stream.mp4"
  }

Data Fields

  • "video_id" is the video identifier in the original dataset where the prompt comes from.
  • "prompt" is the text prompt for text-to-video generation.
  • "major content", "attribute control" and "prompt complexity" are the three orthogonal aspects for categorization.
  • "source" denotes the original dataset where the prompt comes from, which can be "WebVid", "MSRVTT" or "ours".
  • "video_url" is the url link of the reference video.

Dataset Statistics

FETV contains 619 text prompts. The data distributions over different categories are as follows