worldbench/LiDARCrafter
[AAAI 2026 Oral] LiDARCrafter: Dynamic 4D World Modeling from LiDAR Sequences
This project helps self-driving car engineers and researchers create realistic, dynamic 4D LiDAR data for virtual testing environments. By inputting descriptions or existing 3D layouts, it generates detailed LiDAR point cloud sequences that simulate real-world driving scenarios. The output is a highly controllable and spatiotemporally consistent simulation of a dynamic environment, useful for training and validating autonomous vehicle systems.
188 stars.
Use this if you need to generate diverse and controllable 4D LiDAR sequences to rigorously test autonomous driving algorithms in simulated environments.
Not ideal if you are looking for a tool to process static 3D LiDAR scans or perform object detection directly on real-world LiDAR data.
Stars
188
Forks
13
Language
Python
License
MIT
Category
Last pushed
Dec 12, 2025
Commits (30d)
0
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