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--- |
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language: |
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- en |
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pretty_name: Movie Gen Video Benchmark |
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dataset_info: |
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features: |
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- name: prompt |
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dtype: string |
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- name: video |
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dtype: binary |
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splits: |
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- name: test_with_generations |
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num_bytes: 16029316444 |
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num_examples: 1003 |
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- name: test |
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num_bytes: 113706 |
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num_examples: 1003 |
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download_size: 16029724908 |
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dataset_size: 16029430150 |
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configs: |
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- config_name: default |
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data_files: |
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- split: test_with_generations |
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path: data/test_with_generations-* |
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- split: test |
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path: data/test-* |
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--- |
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# Dataset Card for the Movie Gen Benchmark |
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[Movie Gen](https://ai.meta.com/research/movie-gen/) is a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. |
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Here, we introduce our evaluation benchmark "Movie Gen Bench Video Bench", as detailed in the [Movie Gen technical report](https://ai.meta.com/static-resource/movie-gen-research-paper) (Section 3.5.2). |
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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. |
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## Dataset Summary |
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Movie Gen Video Bench consists of 1003 prompts that cover all the different testing aspects/concepts: |
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1. human activity (limb and mouth motion, emotions, etc.) |
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2. animals |
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3. nature and scenery |
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4. physics (fluid dynamics, gravity, acceleration, collisions, explosions, etc.) |
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5. unusual subjects and unusual activities. |
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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. |
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## Dataset Splits |
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We are releasing two versions of the benchmark: |
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1. Test (test): This version includes only the prompts, making it easier to download and use the benchmark. |
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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. |
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## Usage |
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```python |
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from datasets import load_dataset |
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# to download only the prompts |
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dataset = load_dataset("meta-ai-for-media-research/movie_gen_video_bench", split="test") |
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print(dataset[0]) |
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# to download the prompts and movie gen generations |
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dataset = load_dataset("meta-ai-for-media-research/movie_gen_video_bench", split="test_with_generations") |
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print(dataset[0]) |
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# to display a video and a prompt on jupyter notebook |
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import mediapy |
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example = dataset[0] |
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with open("tmp.mp4", "wb") as f: |
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f.write(example["video"]) |
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video = mediapy.read_video("tmp.mp4") |
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print(example["prompt"]) |
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mediapy.show_video(video) |
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``` |
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## Licensing Information |
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Licensed with [CC-BY-NC](https://github.com/facebookresearch/MovieGenBench/blob/main/LICENSE) License. |
