Toytiny/RaFlow
[RA-L & IROS'22] Self-Supervised Scene Flow Estimation with 4-D Automotive Radar
This project helps autonomous vehicles understand the movement of objects around them using 4-D automotive radar data. It takes raw radar point clouds as input and outputs a 'scene flow' map, which shows how each object in the scene is moving. This is especially useful for self-driving car engineers and researchers developing robust navigation systems in challenging weather.
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Use this if you need to determine the arbitrary motion of multiple independent objects from 4-D radar data for autonomous driving applications.
Not ideal if you are working with LiDAR data or require annotated datasets for training, as this method focuses on self-supervised learning with radar.
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75
Forks
12
Language
Python
License
MIT
Category
Last pushed
Mar 18, 2023
Commits (30d)
0
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