| --- |
| license: cc-by-nc-sa-4.0 |
| language: |
| - en |
| tags: |
| - human-trajectory-prediction |
| - jrdb |
| - jta |
| - physics-simulation |
| - paa2026 |
| pipeline_tag: other |
| library_name: pytorch |
| --- |
| |
| # Hexa-P: PAA 2026 release assets |
|
|
| Checkpoints and preprocessed data for |
| **Hexa-P: Physical Plausibility-aware Pre-training for Pedestrian Path Prediction** (Pattern Analysis and Applications, 2026). |
|
|
| 🐙 [code](https://github.com/ImIntheMiddle/Hexa-P) · 🌐 [project page](https://iminthemiddle.github.io/Hexa-P-Page/) |
|
|
| ## Contents |
|
|
| - `weights/stage1/hexap_pretrain.ckpt`: Hexa-P pre-trained in the physics simulation (5 hypotheses), the starting point of fine-tuning |
| - `weights/stage1/hexap_pretrain_deterministic.ckpt`: the same with one hypothesis |
| - `weights/stage1/controller.ckpt`: humanoid controller that walks the pre-training paths |
| - `weights/stage2/{jrdb, jta}/hexap.pt`: Hexa-P fine-tuned on JRDB and JTA |
| - `data/{jta, jrdb, vru}/{train, val, test}/`: preprocessed data (`vru` is the Urban dataset) |
| - `data/jta_replay/test/`: JTA test scenes for the robot navigation experiment |
|
|
| ## Usage |
|
|
| See the [GitHub README](https://github.com/ImIntheMiddle/Hexa-P) for download + setup instructions. |
|
|
| ## License |
|
|
| Research, non-commercial use only. `data/<dataset>/LICENSE` gives the licence of each folder: JTA CC BY-NC 4.0, JRDB CC BY-NC-SA 4.0, Urban CC BY 4.0. The weights were trained with SMPL and AMASS, which restrict commercial use. The JTA authors require the statement: "I declare that I will use the JTA Dataset for research and educational purposes only, since I am aware that commercial use is prohibited. I also undertake to purchase a copy of Grand Theft Auto V." |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{taketsugu2026hexap, |
| title = {Hexa-P: Physical Plausibility-aware Pre-training for Pedestrian Path Prediction}, |
| author = {Taketsugu, Hiromu and Nobuhara, Shohei and Ukita, Norimichi}, |
| journal = {Pattern Analysis and Applications}, |
| year = {2026} |
| } |
| ``` |
|
|
