Hugging Face's logo

Datasets:
lyx97
/
FETV

Tasks:
Text-to-Video
Modalities:
Text
Formats:
json
Languages:
English
Size:
< 1K
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
FETV / README.md
lyx97's picture
lyx97
Update README.md
e9a6c05
preview code
|
raw
history blame contribute delete
2.1 kB
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. caption

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",
  "unusual type": null
  }

Data Fields

  • "video_id": The video identifier in the original dataset where the prompt comes from.
  • "prompt": The text prompt for text-to-video generation.
  • "major content": The major content described in the prompt.
  • "attribute control": The attribute that the prompt aims to control.
  • "prompt complexity": The complexity of the prompt.
  • "source": The original dataset where the prompt comes from, which can be "WebVid", "MSRVTT" or "ours".
  • "video_url": The url link of the reference video.
  • "unusual type": The type of unusual combination the prompt involves. Only available for data instances with "source": "ours".

Dataset Statistics

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) caption caption