ngqtrung/full-modality-bench

Multimodal Video QA Dataset

This dataset contains challenging video question-answering tasks that require understanding both visual and audio information across entire video timelines.

Dataset Statistics

• Total Videos: 4,140
• Total Size: 118.08 GB

Dataset Structure

The dataset is split into multiple parts (each ≤2GB):

• Part 1: 75 videos (1.97 GB) - videos_part001.zip
• Part 2: 49 videos (1.97 GB) - videos_part002.zip
• Part 3: 55 videos (1.91 GB) - videos_part003.zip
• Part 4: 82 videos (1.99 GB) - videos_part004.zip
• Part 5: 81 videos (1.98 GB) - videos_part005.zip
• Part 6: 66 videos (1.98 GB) - videos_part006.zip
• Part 7: 56 videos (1.78 GB) - videos_part007.zip
• Part 8: 66 videos (1.99 GB) - videos_part008.zip
• Part 9: 62 videos (1.97 GB) - videos_part009.zip
• Part 10: 70 videos (2.00 GB) - videos_part010.zip
• Part 11: 68 videos (1.99 GB) - videos_part011.zip
• Part 12: 83 videos (1.97 GB) - videos_part012.zip
• Part 13: 59 videos (1.89 GB) - videos_part013.zip
• Part 14: 58 videos (1.96 GB) - videos_part014.zip
• Part 15: 79 videos (1.97 GB) - videos_part015.zip
• Part 16: 60 videos (1.97 GB) - videos_part016.zip
• Part 17: 70 videos (1.97 GB) - videos_part017.zip
• Part 18: 80 videos (2.00 GB) - videos_part018.zip
• Part 19: 97 videos (1.99 GB) - videos_part019.zip
• Part 20: 78 videos (1.95 GB) - videos_part020.zip
• Part 21: 81 videos (2.00 GB) - videos_part021.zip
• Part 22: 68 videos (1.99 GB) - videos_part022.zip
• Part 23: 61 videos (1.99 GB) - videos_part023.zip
• Part 24: 66 videos (1.92 GB) - videos_part024.zip
• Part 25: 61 videos (1.90 GB) - videos_part025.zip
• Part 26: 66 videos (1.97 GB) - videos_part026.zip
• Part 27: 83 videos (1.97 GB) - videos_part027.zip
• Part 28: 55 videos (1.99 GB) - videos_part028.zip
• Part 29: 84 videos (1.95 GB) - videos_part029.zip
• Part 30: 60 videos (1.94 GB) - videos_part030.zip
• Part 31: 63 videos (1.85 GB) - videos_part031.zip
• Part 32: 59 videos (1.95 GB) - videos_part032.zip
• Part 33: 58 videos (1.96 GB) - videos_part033.zip
• Part 34: 57 videos (1.89 GB) - videos_part034.zip
• Part 35: 64 videos (1.97 GB) - videos_part035.zip
• Part 36: 72 videos (2.00 GB) - videos_part036.zip
• Part 37: 74 videos (1.99 GB) - videos_part037.zip
• Part 38: 64 videos (1.97 GB) - videos_part038.zip
• Part 39: 77 videos (1.98 GB) - videos_part039.zip
• Part 40: 66 videos (1.80 GB) - videos_part040.zip
• Part 41: 58 videos (1.93 GB) - videos_part041.zip
• Part 42: 47 videos (1.97 GB) - videos_part042.zip
• Part 43: 69 videos (1.95 GB) - videos_part043.zip
• Part 44: 69 videos (1.97 GB) - videos_part044.zip
• Part 45: 73 videos (1.93 GB) - videos_part045.zip
• Part 46: 72 videos (1.98 GB) - videos_part046.zip
• Part 47: 73 videos (2.00 GB) - videos_part047.zip
• Part 48: 55 videos (2.00 GB) - videos_part048.zip
• Part 49: 68 videos (1.99 GB) - videos_part049.zip
• Part 50: 79 videos (1.99 GB) - videos_part050.zip
• Part 51: 52 videos (1.80 GB) - videos_part051.zip
• Part 52: 86 videos (1.98 GB) - videos_part052.zip
• Part 53: 88 videos (1.99 GB) - videos_part053.zip
• Part 54: 74 videos (1.97 GB) - videos_part054.zip
• Part 55: 62 videos (1.98 GB) - videos_part055.zip
• Part 56: 81 videos (1.98 GB) - videos_part056.zip
• Part 57: 75 videos (1.93 GB) - videos_part057.zip
• Part 58: 70 videos (2.00 GB) - videos_part058.zip
• Part 59: 69 videos (1.95 GB) - videos_part059.zip
• Part 60: 68 videos (1.98 GB) - videos_part060.zip
• Part 61: 19 videos (0.64 GB) - videos_part061.zip

Metadata: All video metadata is in a single file metadata.json

Question Types

The dataset includes 8 question types testing global video understanding:

1. Temporal: Questions about timing and sequence across the video
2. Causal: Cause-effect relationships spanning multiple segments
3. Plot: Overall narrative arc from beginning to end
4. Cross-modality: Patterns emerging from visual + audio combination
5. Emotional: Emotional journeys across the timeline
6. Time Order: Sequence of major events
7. Existence: Recurring patterns throughout the video
8. Scene Description: Scene progression across segments

Question Variants

Each video has 3 question variants:

1. Default: All information is correct (4 choices: A-D)
2. Audio Misleading: Subtle errors in sound/speech information (5 choices: A-E, correct answer is E "None of the above")
3. Visual Misleading: Subtle errors in visual/action information (5 choices: A-E, correct answer is E "None of the above")

Metadata Format

The single metadata.json file contains all video metadata:

{
  "video_id_1": {
    "video_id": "video_id_1",
    "video_duration": "120s",
    "duration": "1-2min",
    "num_segments": 12,
    "question_type": "temporal",
    "task0": {
      "variant_type": "default",
      "question": "...",
      "answer": "B",
      "candidates": ["A. ...", "B. ...", "C. ...", "D. ..."],
      "reasoning": "..."
    },
    "task1": {
      "variant_type": "audio_misleading",
      "question": "...",
      "answer": "E",
      "candidates": ["A. ...", "B. ...", "C. ...", "D. ...", "E. None of the above"],
      "reasoning": "..."
    },
    "task2": {
      "variant_type": "visual_misleading",
      "question": "...",
      "answer": "E",
      "candidates": ["A. ...", "B. ...", "C. ...", "D. ...", "E. None of the above"],
      "reasoning": "..."
    }
  },
  "video_id_2": {
    ...
  }
}

Usage

import json
import zipfile

# Load metadata for ALL videos
with open('metadata.json', 'r') as f:
    metadata = json.load(f)

# Extract all video zip files
for zip_file in ['videos_part001.zip', 'videos_part002.zip', ...]:
    with zipfile.ZipFile(zip_file, 'r') as zip_ref:
        zip_ref.extractall('videos/')

# Access QA data
for video_id, data in metadata.items():
    print(f"Video: {video_id}")
    print(f"Question: {data['task0']['question']}")
    print(f"Answer: {data['task0']['answer']}")

# Or access specific video
video_data = metadata['specific_video_id']
print(f"Default question: {video_data['task0']['question']}")
print(f"Audio misleading: {video_data['task1']['question']}")
print(f"Visual misleading: {video_data['task2']['question']}")

Citation

If you use this dataset, please cite:

@dataset{multimodal_video_qa,
  title={Multimodal Video QA Dataset},
  year={2025},
  publisher={HuggingFace}
}

License

MIT License