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--- |
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pretty_name: K600 Frozen Test Clips (for GRW Smoothing) |
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language: en |
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license: other |
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task_categories: |
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- video-classification |
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tags: |
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- kinetics-600 |
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- video |
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- webdataset |
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- evaluation |
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--- |
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# K600 Frozen Test Clips (for reproducible evaluation) |
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This repository provides a **frozen** set of extracted clips used for evaluation in the paper: |
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## Paper |
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- https://huggingface.co/papers/2511.20928 |
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- https://arxiv.org/abs/2511.20928 |
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## Why this dataset exists |
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Kinetics videos are hosted on YouTube, and availability can change over time. This dataset exists to provide a **stable evaluation set** aligned with the paper’s experiments. |
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## What’s included |
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- `k600_test_ds.tar.gz` — an archive containing extracted test clips organized by class. |
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## Code (reproduction instructions) |
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For the **exact, step-by-step instructions** to reproduce results (expected directory layout, caching, and evaluation pipeline), please refer to: |
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- https://github.com/cmusatyalab/grw-smoothing |
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## Related model weights |
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- https://huggingface.co/DrGil/grw-smoothing-movinet |
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## Licensing / redistribution note |
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This dataset is marked as `other` because it is derived from Kinetics/YouTube-sourced videos and may involve varying rights. Please ensure your usage complies with the original rights and applicable terms. |
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## Citation |
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If you use this dataset, please cite: |
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```bibtex |
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@inproceedings{goldman2025grwsmoothing, |
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title = {Smooth Regularization for Efficient Video Recognition}, |
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author = {Gil Goldman and Raja Giryes and Mahadev Satyanarayanan}, |
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booktitle = {Advances in Neural Information Processing Systems (NeurIPS)}, |
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year = {2025}, |
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url = {https://arxiv.org/abs/2511.20928} |
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} |
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