| license: cc-by-4.0 | |
| task_categories: | |
| - robotics | |
| tags: | |
| - sketchy | |
| - open-x | |
| # Sketchy 128x128 | |
| This dataset is a pre-processed version of the Sketchy dataset (originally from DeepMind and the Open-X Embodiment effort) used in the paper [Latent Particle World Models: Self-supervised Object-centric Stochastic Dynamics Modeling](https://huggingface.co/papers/2603.04553). | |
| The data has been pre-processed to 128x128 pixels. Unlike the original TFRecords, this version consists of raw frames/images, facilitating use in standard PyTorch/JAX pipelines for training object-centric world models. | |
| - **Project Page:** [https://taldatech.github.io/lpwm-web](https://taldatech.github.io/lpwm-web) | |
| - **GitHub Repository:** [https://github.com/taldatech/lpwm](https://github.com/taldatech/lpwm) | |
| ## Usage | |
| To train the Latent Particle World Model (LPWM) on the Sketchy dataset, you can use the following command from the [official repository](https://github.com/taldatech/lpwm): | |
| ```bash | |
| python train_lpwm.py --dataset sketchy | |
| ``` | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{ | |
| daniel2026latent, | |
| title={Latent Particle World Models: Self-supervised Object-centric Stochastic Dynamics Modeling}, | |
| author={Tal Daniel and Carl Qi and Dan Haramati and Amir Zadeh and Chuan Li and Aviv Tamar and Deepak Pathak and David Held}, | |
| booktitle={The Fourteenth International Conference on Learning Representations}, | |
| year={2026}, | |
| url={https://openreview.net/forum?id=lTaPtGiUUc} | |
| } | |
| ``` |