yanx27/2DPASS
2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds (ECCV 2022) :fire:
This project helps self-driving car developers and robotics engineers analyze LiDAR sensor data by automatically classifying objects in a 3D point cloud. It takes raw LiDAR scans and corresponding 2D camera images as input, then identifies and labels elements like roads, vehicles, and pedestrians in the 3D environment. This allows for more precise understanding of surroundings for autonomous navigation.
463 stars. No commits in the last 6 months.
Use this if you need to accurately identify and label objects within 3D LiDAR point clouds for applications in autonomous driving or robotics, especially when you can also leverage corresponding 2D camera images.
Not ideal if your primary need is object detection from 2D images only, or if you don't have access to both LiDAR point clouds and synchronized 2D camera data.
Stars
463
Forks
57
Language
Python
License
MIT
Category
Last pushed
Apr 22, 2023
Commits (30d)
0
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