YoushaaMurhij/FMFNet
Pytorch implementation for the paper: "FMFNet: Improve the 3D Object Detection and Tracking via Feature Map Flow" [IJCNN-2022]
This project helps autonomous systems and robots more accurately understand their surroundings by detecting and tracking 3D objects like vehicles, pedestrians, and cyclists from real-time point cloud data. It takes raw 3D sensor data as input and outputs precise locations and movements of objects. This is for engineers and researchers developing self-driving vehicles, robotic navigation, or advanced sensor analysis systems.
No commits in the last 6 months.
Use this if you need to significantly improve the accuracy and reliability of 3D object detection and tracking in dynamic environments using point cloud data.
Not ideal if your application primarily involves 2D image analysis or does not rely on real-time 3D point cloud data.
Stars
39
Forks
3
Language
Python
License
MIT
Category
Last pushed
Oct 28, 2022
Commits (30d)
0
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