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README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - video-text-to-text
+  - visual-question-answering
+language:
+  - en
+tags:
+  - video
+  - social-interaction
+  - benchmark
+  - multi-person
+  - gaze
+  - gesture-recognition
+size_categories:
+  - 1K<n<10K
+---
+
+# Social Benchmark Dataset
+
+## Description
+
+Social Benchmark is a video-based social understanding benchmark dataset containing **6,433 video clips** from 3 evaluation sets: MMSI, Online-MMSI, and original TVQA+. Each benchmark tests different aspects of social reasoning in multi-person video scenarios.
+
+## Dataset Statistics
+
+| Benchmark | Videos | Size | JSON Files |
+|-----------|--------|------|------------|
+| MMSI | 1,708 | ~377 MB | 3 (mpp, pcr, sti) |
+| Online-MMSI | 1,708 | ~2.9 GB | 3 (mpp, pcr, sti) |
+| original TVQA+ | 3,017 | ~540 MB | 1 (eval) |
+| **Total** | **6,433** | **~3.8 GB** | **7** |
+
+## Benchmark Tasks
+
+- **MPP** (Multi-Person Prediction): Predict social behaviors of multiple persons
+- **PCR** (Person-Centric Reasoning): Reason about individual person's social role
+- **STI** (Social Temporal Inference): Infer social dynamics over time
+- **TVQA+**: Video question answering with spatial-temporal grounding
+
+## Dataset Structure
+
+```
+social-benchmark/
+├── json/
+│   ├── mmsi_test_mpp_original.json
+│   ├── mmsi_test_pcr_original.json
+│   ├── mmsi_test_sti_original.json
+│   ├── online_mmsi_test_mpp_extended.json
+│   ├── online_mmsi_test_pcr_extended.json
+│   ├── online_mmsi_test_sti_extended.json
+│   └── tvqa_plus_eval.json
+└── tars/
+    ├── mmsi_videos_part001.tar
+    ├── online_mmsi_videos_part001.tar
+    └── original_tvqa_plus_videos_part001.tar
+```
+
+## Usage
+
+```python
+from huggingface_hub import snapshot_download
+
+# Download everything
+snapshot_download(
+    repo_id="arkimjh/social-benchmark",
+    repo_type="dataset",
+    local_dir="./social-benchmark"
+)
+
+# Extract video archives
+import tarfile
+from pathlib import Path
+
+for tar_file in Path("./social-benchmark/tars").glob("*.tar"):
+    with tarfile.open(tar_file) as tf:
+        tf.extractall("./social-benchmark/videos/")
+```
+
+## Data Sources
+
+- **MMSI**: Multi-Modal Social Interaction benchmark (offline setting, original videos)
+- **Online-MMSI**: Multi-Modal Social Interaction benchmark (online setting, original videos)
+- **original TVQA+**: TV show QA with compositional spatio-temporal grounding (original videos)
+
+## Citation
+
+TBD