license: mit
language:
- en
size_categories:
- n<1K
tags:
- benchmark
- world-model
- video-generation
- programmable-world-models
arxiv: '2610.02205'
pretty_name: PROWBench — Episodes
configs:
- config_name: default
default: true
data_files:
- split: full
path: splits/full.parquet
- split: verified_first_frame
path: splits/verified_first_frame.parquet
- split: unverified_first_frame
path: splits/unverified_first_frame.parquet
- split: long_video
path: splits/long_video.parquet
- split: multi_view
path: splits/multi_view.parquet
- split: gunfight
path: splits/gunfight.parquet
PROWBench Dataset
PROWBench evaluates whether video models follow program-specified motion and interactions. It contains 170 episodes, 200 camera views, and 600 proxy videos, with prompts, recorded world states, and RGB first frames where available.
Paper · Project · Gallery · Code · Evaluation guide
Download
pip install -U huggingface_hub
hf download AlayaLab/PROWBench --repo-type dataset --local-dir PROWBench
Load sample metadata and preview images in Python (pip install -U datasets pillow):
from datasets import load_dataset
dataset = load_dataset("AlayaLab/PROWBench")
sample = dataset["full"][0]
The *_file fields contain paths relative to the dataset root. Use the download command above for the full videos, prompts and engine records.
Data
| Split | Episodes | Duration | RGB first frames |
|---|---|---|---|
verified_first_frame |
40 | 5 s | 40 |
unverified_first_frame |
90 | 5 s | 0 |
long_video |
10 | 30 s | 0 |
multi_view |
10 | 5 s | 0 |
gunfight |
20 | 5 s | 20 |
Each view has three proxy representations: white (coarse 3D), mixed (semantic proxy), and colored-obb (3D boxes). Multi-view episodes have four synchronized cameras.
The full Viewer split contains 600 rows, one per camera–representation pair; the other splits are subsets. Full prompts are available through prompt_file. preview_kind distinguishes RGB first-frame references from proxy previews.
A typical episode:
episodes/<group>/<episode>/
├── manifest.json
├── scene/ # Recorded world states
├── cameras/ # Camera records
└── views/<camera>/
├── <representation>/video.mp4
├── <representation>/prompt.txt
├── prompt-context/first_frame.png # When available
└── visibility.json # Multi-view
Long-video prompts use JSON files or a prompts/ directory of windowed prompts. Use prompt_file and the adjacent sample.json for exact input paths, including versioned episodes.
This release contains conditioning inputs and annotations; raw depth maps and generated model outputs are not included. Release metadata · Sample metadata.
License
This dataset is released under the MIT License.
Citation
If you find PROWBench helpful for your research, please consider citing our paper:
@misc{huang2026prowbench,
title={PROWBench: Do Video Models Render What the Program Specifies?},
author={Zheng-Hui Huang and Guixu Lin and Yu-Ju Tsai and Jian-Kai Zhu and Fengbo Lan and Yu-Lun Liu and Yung-Yu Chuang and Kaipeng Zhang and Zhixiang Wang},
year={2026},
eprint={2610.02205},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2610.02205}
}