SamirAbouHaidar/HARP-NeXt
[IROS 2025] HARP-NeXt: High-Speed and Accurate Range-Point Fusion Network for 3D LiDAR Semantic Segmentation
This project helps self-driving car engineers and robotics researchers quickly and accurately identify objects in 3D environments using LiDAR sensor data. It takes raw 3D point cloud data from LiDAR scans as input and outputs a segmented scene where each point is labeled with what it represents (e.g., car, pedestrian, road, tree). This allows for robust perception and scene understanding in autonomous systems.
Use this if you need to process 3D LiDAR data in real-time on both powerful workstations and embedded systems like NVIDIA Jetson AGX Orin for tasks like autonomous navigation or robotic sensing.
Not ideal if your primary data source is visual camera imagery, as this tool is specifically designed for LiDAR 3D point cloud segmentation.
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14
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2
Language
Python
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Last pushed
Dec 22, 2025
Commits (30d)
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