Create README.md

README.md

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+---
+license: cc-by-nc-sa-4.0
+language:
+- en
+---
+
+# OWM-95 Benchmark
+
+[![Project Page](https://img.shields.io/badge/Project-Page-blue)](https://compvis.github.io/myriad)
+[![Paper](https://img.shields.io/badge/arXiv-paper-b31b1b)](_blank)
+[![MYRIAD Weights](https://img.shields.io/badge/HuggingFace-Weights-orange)](https://huggingface.co/CompVis/myriad)
+
+## Abstract
+
+The OWM-95 benchmark was proposed in the paper [Envisioning the Future, One Step at a Time](_blank) and used to evaluate the [MYRIAD](https://huggingface.co/CompVis/myriad/) model.
+
+OWM-95 is a benchmark of 95 curated videos with motion annotations, where the distribution of motion is constrained to make evaluation of probabilistic motion prediction methods feasible.
+Videos are obtained from Pexels ([Pexels License](https://www.pexels.com/license/)), we manually annotate relevant objects, and the type of motion observed. We use an off-the-shelf tracker to obtain motion trajectories and manually verify correctness.
+
+## Project Page and Code
+
+- **Project Page**: https://compvis.github.io/myriad
+- **GitHub Repository**: https://github.com/CompVis/flow-poke-transformer
+
+## Usage
+
+We provide code to run the OWM evaluation in our [GitHub repository](https://github.com/CompVis/flow-poke-transformer).
+
+To run the evaluation, first download the data by running `hf download CompVis/omw-95 --repo-type dataset` then run the evaluation script via
+```shell
+python -m scripts.eval.myriad_eval.owm --checkpoint-path path/to/checkpoint  -data-path path/to/data
+```
+
+## License
+
+- Videos are sourced from Pexels and thus licensed under the [Pexels License](https://www.pexels.com/license/)
+- Metadata and motion annotations are provided under the [CC-BY-NC-SA-44.0](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en) license
+
+## Citation
+
+If you find our data or code useful, please cite our paper:
+
+```bibtex
+@inproceedings{baumann2025whatif,
+    title={What If: Understanding Motion Through Sparse Interactions}, 
+    author={Stefan Andreas Baumann and Nick Stracke and Timy Phan and Bj{\"o}rn Ommer},
+    booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
+    year={2025}
+}
+```