HuangCongQing/3D-Point-Clouds
🔥3D点云目标检测&语义分割(深度学习)-SOTA方法,代码,论文,数据集等
This resource collects state-of-the-art methods, code, papers, and datasets for analyzing 3D point cloud data. It focuses on identifying objects and classifying regions within these 3D scans. Autonomous driving engineers, robotics researchers, and anyone working with 3D sensor data to understand real-world environments would find this valuable.
604 stars. No commits in the last 6 months.
Use this if you are developing or researching autonomous driving perception systems that rely on interpreting 3D sensor data to detect objects or understand scenes.
Not ideal if you are looking for a ready-to-use, off-the-shelf software application for general 3D modeling or non-AI-driven point cloud processing.
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604
Forks
85
Language
Jupyter Notebook
License
MIT
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Last pushed
Jan 20, 2025
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