hancyran/LiDAR-Diffusion
[CVPR 2024] Official implementation of "Towards Realistic Scene Generation with LiDAR Diffusion Models"
This project helps robotics engineers and autonomous vehicle developers create realistic, synthetic LiDAR scan data. It takes existing LiDAR point cloud data and generates new, diverse, and high-quality LiDAR scans that mimic real-world scenarios. This is useful for expanding datasets for training and testing autonomous systems without needing to collect more physical data.
279 stars. No commits in the last 6 months.
Use this if you need to generate highly realistic, synthetic 3D LiDAR point clouds to augment your training datasets for autonomous vehicles or robotics, especially when real-world data collection is costly or limited.
Not ideal if you are looking to process or analyze existing LiDAR data for tasks like object detection or mapping, rather than generating new synthetic data.
Stars
279
Forks
18
Language
Python
License
MIT
Category
Last pushed
May 21, 2024
Commits (30d)
0
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