MYRIAD-Physics

MYRIAD-Physics extends Physics-IQ and Physion with motion annotations and object tracks for evaluating probabilistic future trajectory forecasting under physical interactions. It was presented in the paper Envisioning the Future, One Step at a Time.

Abstract

MYRIAD-Physics extends Physics-IQ and Physion with motion annotations and object tracks (following the same approach proposed in CompVis/owm-95) for evaluating probabilistic future trajectory forecasting under physical interactions.

Unlike 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.

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.

To run the benchmark evaluation for this dataset, you can use the following command:

python -m scripts.myriad_eval.openset_prediction --data-root path/to/data  --ckpt-path path/to/checkpoint --dataset-name [owm | physion | physics-iq]

Citation

If you find our data or code useful, please cite our paper:

@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}
}