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README.md

@@ -1,3 +1,48 @@
----
-license: cc-by-nc-sa-4.0
----
+---
+license: cc-by-nc-sa-4.0
+task_categories:
+- video-prediction
+- object-tracking
+language:
+- en
+pretty_name: MYRIAD-Physics
+size_categories:
+- 1K<n<10K
+---
+
+# MYRIAD-Physics
+
+[![Project Page](https://img.shields.io/badge/Project-Page-blue)](https://compvis.github.io/myriad)
+[![Paper](https://img.shields.io/badge/Paper-CVPR%202026-red)]([INSERT_PAPER_LINK])
+[![OWM Benchmark](https://img.shields.io/badge/Related-OWM--95-green)](https://huggingface.co/datasets/CompVis/owm-95)
+
+
+## Abstract
+
+MYRIAD-Physics extends Physics-IQ and Physion with motion annotations and object tracks (following the same approach proposed in [`CompVis/owm-95`](https://huggingface.co/datasets/CompVis/owm-95)) for evaluating probabilistic future trajectory forecasting under physical interactions.
+
+Unlike [`CompVis/owm-95`](https://huggingface.co/datasets/CompVis/owm-95), which distributes videos together with annotations, this repository provides only the additional metadata: annotations and trajectories for videos that must be obtained separately using [this download script](https://github.com/CompVis/flow-poke-transformer/blob/main/scripts/myriad_eval/download_datasets.sh).
+
+We manually annotate relevant objects and the type of motion observed, and we use an off-the-shelf tracker to obtain motion trajectories with manual verification of 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 and instructions to download the dataset and run the MYRIAD evaluation in our [GitHub repository](https://github.com/CompVis/flow-poke-transformer).
+
+## Citation
+
+If you find our data or code useful, please cite our paper:
+
+```bibtex
+@inproceedings{baumann2026envisioning,
+  title={Envisioning the Future, One Step at a Time},
+  author={Baumann, Stefan Andreas and Wiese, Jannik and Martorella, Tommaso and Kalayeh, Mahdi M. and Ommer, Bjorn},
+  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  year={2026}
+}
+```

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