This dataset contains only annotations. Users must separately obtain the source videos from Ego-Exo4D, CMU Panoptic Studio, and MMPTRACK under each dataset's original license. Commercial use is restricted due to source-dataset terms.

Multi-View Video QA Dataset

This dataset contains 1,323 question-answer pairs across 608 multi-view video samples for video question answering research.

Repository Structure

.
├── annotations/
│   ├── README.md                 # This file
│   ├── all_questions.json        # QA annotations (original format)
│   ├── all_questions.parquet     # QA annotations (parquet format)
│   ├── video_mapping.csv         # Video file mapping (source -> target)
│   └── prepare_videos.py         # Script to prepare videos from source datasets
│
├── dataset/                      # Source datasets (user must download)
│   ├── egoexo/
│   │   └── takes/
│   │       ├── sfu_basketball_01_10/
│   │       │   └── frame_aligned_videos/
│   │       │       └── downscaled/
│   │       │           └── 448/
│   │       │               ├── aria01_1201-1.mp4
│   │       │               ├── cam01.mp4
│   │       │               └── ...
│   │       └── ...
│   │
│   ├── mmptrack/
│   │   ├── train/
│   │   │   └── videos/
│   │   │       ├── 63am/
│   │   │       │   └── cafe_shop_0/
│   │   │       │       ├── cafe_shop_0_camera1.mp4
│   │   │       │       └── ...
│   │   │       └── 64am/
│   │   └── validation/
│   │       └── videos/
│   │           └── 64pm/
│   │
│   └── panoptic/
│       ├── 160224_haggling1/
│       │   └── hdVideos_down/
│       │       ├── hd_00_00.mp4
│       │       └── ...
│       └── ...
│
└── videos/                       # Prepared videos (output of prepare_videos.py)
    ├── sfu_basketball_05_35_view0.mp4
    ├── sfu_basketball_05_35_view1.mp4
    ├── 63am_cafe_shop_0_view0.mp4
    ├── 160224_haggling1_view0.mp4
    └── ...

Annotation Files

`all_questions.json` / `all_questions.parquet`

Column	Description
`sample_name`	Video sample identifier
`views`	List of view indices used for the question (e.g., `[3, 2]`)
`question`	Question text
`choice_A`, `choice_B`, `choice_C`, `choice_D`	Multiple choice options
`correct_answer`	Correct answer key (A/B/C/D)
`gt_answer_text`	Ground truth answer text
`category`	Question category
`static_or_dynamic`	Static or dynamic scene
`timestamp_start`, `timestamp_end`	Relevant time range (seconds)
`question_type`	Type: counting, descriptive, binary
`original_negated`	Original or negated question

`video_mapping.csv`

Maps 3,088 video files from source datasets to standardized names:

Column	Description
`target`	Target filename (e.g., `sfu_basketball_05_35_view0.mp4`)
`sample_name`	Sample name
`view`	View number
`dataset`	Source dataset: `egoexo`, `mmptrack`, `panoptic`
`split`	For mmptrack: `train` or `validation`
`source_rel_path`	Relative path within source dataset
`source_file`	Source filename

Preparing Videos

Due to licensing restrictions, videos are not included. You must download them from the original sources and use the provided script to prepare them.

Step 1: Download Source Datasets

Ego-Exo4D (2,590 files)
- Website: https://ego-exo4d-data.org/
- Download the takes with frame_aligned_videos/downscaled/448/ videos
MMPTrack (272 files)
- Website: https://iccv2021-mmp.github.io/subpage/dataset.html
- Download both train and validation splits
CMU Panoptic (220 files)
- Website: http://domedb.perception.cs.cmu.edu/
- Download sequences with hdVideos_down/ (downscaled HD videos)

Step 2: Organize Directory Structure

Place downloaded datasets under dataset/ directory following the structure shown above.

Step 3: Run the Preparation Script

# Preview first
python annotations/prepare_videos.py \
    --dataset-root ./dataset \
    --output-dir ./videos \
    --dry-run

# Copy files
python annotations/prepare_videos.py \
    --dataset-root ./dataset \
    --output-dir ./videos

# Or create symlinks (saves disk space)
python annotations/prepare_videos.py \
    --dataset-root ./dataset \
    --output-dir ./videos \
    --symlink

Statistics

Dataset	Samples	Video Files	Categories
Ego-Exo4D	496	2,590	Basketball, cooking, bouldering, dance, music, etc.
MMPTrack	68	272	Cafe, retail, office, lobby, industry safety
CMU Panoptic	44	220	Haggling, mafia, ultimatum, social games
Total	608	3,082

Citation

If you use this dataset, please cite the original source datasets:

@article{grauman2024egoexo4d,
  title={Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives},
  author={Grauman, Kristen and others},
  journal={CVPR},
  year={2024}
}

@inproceedings{han2021mmptrack,
  title={MMPTrack: Large-scale Densely Annotated Multi-camera Multiple People Tracking Benchmark},
  author={Han, Xiaotian and others},
  booktitle={ICCV Workshop},
  year={2021}
}

@inproceedings{joo2015panoptic,
  title={Panoptic Studio: A Massively Multiview System for Social Motion Capture},
  author={Joo, Hanbyul and others},
  booktitle={ICCV},
  year={2015}
}

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