README.md

metadata

language:
  - en
pretty_name: Movie Gen Video Benchmark
dataset_info:
  features:
    - name: prompt
      dtype: string
    - name: video
      dtype: binary
  splits:
    - name: test_with_generations
      num_bytes: 16029316444
      num_examples: 1003
    - name: test
      num_bytes: 113706
      num_examples: 1003
  download_size: 16029724908
  dataset_size: 16029430150
configs:
  - config_name: default
    data_files:
      - split: test_with_generations
        path: data/test_with_generations-*
      - split: test
        path: data/test-*

Dataset Card for the Movie Gen Benchmark

Movie Gen is a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. Here, we introduce our evaluation benchmark "Movie Gen Bench Video Bench", as detailed in the Movie Gen technical report (Section 3.5.2).

To enable fair and easy comparison to Movie Gen for future works on these evaluation benchmarks, we additionally release the non cherry-picked generated videos from Movie Gen on Movie Gen Video Bench.

Dataset Summary

Movie Gen Video Bench consists of 1003 prompts that cover all the different testing aspects/concepts:

1. human activity (limb and mouth motion, emotions, etc.)
2. animals
3. nature and scenery
4. physics (fluid dynamics, gravity, acceleration, collisions, explosions, etc.)
5. unusual subjects and unusual activities. Besides a comprehensive coverage of different key testing aspects, the prompts also have a good coverage of high/medium/low motion levels at the same time.

Dataset Splits

We are releasing two versions of the benchmark:

1. Test (test): This version includes only the prompts, making it easier to download and use the benchmark.
2. Test with Generations (test_with_generations): This version includes both the prompts and the Movie Gen model’s outputs, allowing for comparative evaluation against the Movie Gen model.

Usage

from datasets import load_dataset

# to download only the prompts
dataset = load_dataset("facebook/moviegen_video", split="test")
print(dataset[0])

# to download the prompts and movie gen generations
dataset = load_dataset("facebook/moviegen_video", split="test")
print(dataset[0])

# to display a video and a prompt on jupyter notebook
import mediapy

example = dataset[0]
with open("tmp.mp4", "wb") as f:
    f.write(example["video"])

video = mediapy.read_video("tmp.mp4")
print(example["prompt"])
mediapy.show_video(video)

Licensing Information

Licensed with CC-BY-NC License.