Datasets:
Tasks:
Video Classification
Formats:
csv
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
medical
License:
Upload folder using huggingface_hub
Browse files- README.md +8 -20
- splits/cs/mcfd/test.csv +1 -0
- splits/cs/mcfd/val.csv +1 -0
- splits/cv/caucafall/test.csv +1 -0
- splits/cv/caucafall/val.csv +1 -0
README.md
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---
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license: cc-by-nc-4.0
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task_categories:
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- video-classification
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language:
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- en
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tags:
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- medical
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pretty_name: 'OmniFall: A Unified Benchmark for Staged-to-Wild Fall Detection'
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size_categories:
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- 10K<n<100K
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---
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# OmniFall: A Unified Benchmark for Staged-to-Wild Fall Detection
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[](https://creativecommons.org/licenses/by-nc-sa/4.0/)
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This benchmark includes annotations for the following datasets:
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1. **CMDFall** (7h 7m) - Multi-subject, multi-view dataset
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2. **UP Fall** (4h 35m) - Multiple subjects with
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3. **Le2i** (47m) - Multiple room settings
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4. **GMDCSA24** (21m) -
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5. **CAUCAFall** (16m)
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6. **OCCU** (14m) -
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7. **EDF** (13m) -
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8. **MCFD** (12m) - Single subject, eight camera views
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9. **OOPS-Fall** - Curated subset of genuine
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## Structure
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## Citation
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If you use OmniFall in your research, please cite our paper
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```bibtex
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@inproceedings{omnifall2025,
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## Contact
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For questions about the dataset, please contact [david.schneider@kit.edu].
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# OmniFall: A Unified Benchmark for Staged-to-Wild Fall Detection
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[](https://creativecommons.org/licenses/by-nc-sa/4.0/)
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This benchmark includes annotations for the following datasets:
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1. **CMDFall** (7h 7m) - Multi-subject, multi-view dataset
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2. **UP Fall** (4h 35m) - Multiple subjects with varied camera views
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3. **Le2i** (47m) - Multiple room settings
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4. **GMDCSA24** (21m) - Varied lighting conditions
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5. **CAUCAFall** (16m) - Includes day/night recordings
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6. **OCCU** (14m) - Depth camera recordings
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7. **EDF** (13m) - Depth camera recordings
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8. **MCFD** (12m) - Single subject, eight camera views
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9. **OOPS-Fall** - Curated subset of genuine accidents from the OOPS dataset
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## Structure
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## Citation
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If you use OmniFall in your research, please cite our paper:
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```bibtex
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@inproceedings{omnifall2025,
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## Contact
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For questions about the dataset, please contact [david.schneider@kit.edu].
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