---
license: cc-by-4.0
task_categories:
  - visual-question-answering
  - video-text-to-text
language:
  - en
tags:
  - video
  - spatial-intelligence
  - multimodal
  - benchmark
size_categories:
  - 1K<n<10K
---

# MMSI-Video-Bench

A video-based spatial intelligence benchmark for evaluating Multimodal Large Language Models (MLLMs).

## Dataset Description

MMSI-Video-Bench tests models on:
- Spatial reasoning
- Motion understanding  
- Planning and prediction
- Cross-video reasoning

## Dataset Structure

```
MMSI-Video-Bench/
├── data/
│   └── test-00000-of-00001.parquet   # 1106 samples
├── frames.zip                         # Extracted video frames
├── ref_images.zip                     # Reference images
├── videos.zip                         # Original videos
└── README.md
```

### Parquet Columns

| Column | Type | Description |
|--------|------|-------------|
| `id` | string | Unique question ID (e.g., "question_0000") |
| `type` | string | Question category |
| `system_prompt` | string | System prompt |
| `task_prompt` | string | Task description |
| `user_prompt` | string | User question |
| `format_prompt` | string | Answer format instructions |
| `ori_question` | string | Original question text |
| `options` | list[string] | Answer choices (A-F) |
| `ground_truth` | string | Correct answer letter |
| `video_list` | list[dict] | Video metadata (path, start, end, base_fps) |
| `frames_list` | list[list[string]] | Paths to extracted frames per video |
| `ref_images` | list[string] | Paths to reference images |

## Usage

```python
import pandas as pd
from datasets import load_dataset

# Option 1: Load parquet directly
df = pd.read_parquet("hf://datasets/oscarqjh/MMSI-Video-Bench/data/test-00000-of-00001.parquet")

# Option 2: Load with datasets library
dataset = load_dataset("oscarqjh/MMSI-Video-Bench")

# Access a sample
sample = dataset["train"][0]
print(sample["id"])
print(sample["ori_question"])
print(sample["options"])
print(sample["ground_truth"])

# Video paths are relative to the extracted zip files
# e.g., sample["video_list"][0]["path"] = "question_0000/video.mp4"
# After extracting videos.zip: videos/question_0000/video.mp4
```

### Extracting Media Files

```bash
# Download and extract
wget https://huggingface.co/datasets/oscarqjh/MMSI-Video-Bench/resolve/main/frames.zip
wget https://huggingface.co/datasets/oscarqjh/MMSI-Video-Bench/resolve/main/ref_images.zip
wget https://huggingface.co/datasets/oscarqjh/MMSI-Video-Bench/resolve/main/videos.zip

unzip frames.zip -d frames/
unzip ref_images.zip -d ref_images/
unzip videos.zip -d videos/
```

## Citation

Please cite the original MMSI-Video-Bench paper if you use this dataset.

## License

CC-BY-4.0