simplexsigil2/wanfall
WanFall is a large-scale synthetic activity recognition dataset designed for fall detection and activities of daily living research. The dataset features computer-generated videos of human actors performing various activities in controlled virtual environments. **Key Features:** - 12,000 video clips with dense temporal annotations - 16 activity classes including falls, posture transitions, and static states - 19,228 temporal segments with frame-level precision - 5.0625 seconds per video clip (81 frames @ 16 fps) - Rich demographic metadata (soft labels): age, gender, ethnicity, body type, heig
| Author / organization | simplexsigil2 |
|---|---|
| License (as declared) | cc-by-nc-4.0 |
| Downloads | 158 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 27 October 2025 |
| Last updated at source | 24 February 2026 |
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