scene_name string | url string | roads list | sidewalks list | pedestrian_traj list | vehicle_traj list |
|---|---|---|---|---|---|
NYC_East_Village | https://www.fab.com/listings/3cd8585d-8279-4e54-a538-09069da61e1f | [{"object_id":"Road_6x6_32","status":"ok","guid":"9EB92B8F41D7BAE60767D1B1E82E9BD3","aabb":{"center"(...TRUNCATED) | [{"object_id":"Sidewalk_4x4_B_9","status":"ok","guid":"7215E10143B05D82E1A53899940F5C89","aabb":{"ce(...TRUNCATED) | [{"start":{"object_id":"SkeletalMeshActor_2","status":"ok","guid":"030D651B4EB71750C497FF9856D46AC2"(...TRUNCATED) | [{"start":{"object_id":"BP_Suv_Car_01_2","status":"ok","guid":"120D32AE49EF86EF166DBB81A3E3A696","aa(...TRUNCATED) |
LychSim Scenes Dataset
Project Page | Paper | GitHub
LychSim is a highly controllable and interactive simulation framework built upon Unreal Engine 5 for vision research. This dataset contains scene-level procedural rules for the simulator.
Description
For each scene, we capture structural priors — navigable floor spaces, road areas, pedestrian walks, and dynamic vehicle / pedestrian trajectories — as structured records keyed to the underlying placed actors. These spatial priors guide the procedural generation process, ensuring that newly synthesized layouts remain faithful to the original scene semantics.
Sample Usage
You can load the dataset using the Hugging Face datasets library:
from datasets import load_dataset
scenes = load_dataset("wufeim/lychsim_scenes")
Citation
If you find our work useful for your research, please consider citing our work:
@article{ma2026lychsim,
title={LychSim: A Controllable and Interactive Simulation Framework for Vision Research},
author={Ma, Wufei and Wang, Chloe and Chen, Siyi and Peng, Jiawei and Li, Patrick and Yuille, Alan},
journal={arXiv preprint arXiv:2605.12449},
year={2026}
}
License
This dataset is released under the Creative Commons Attribution 4.0 International license (CC BY 4.0).
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