QingyongHu/SQN
SQN in Tensorflow (ECCV'2022)
This project helps urban planners, architects, or autonomous vehicle developers automatically identify objects and features within large-scale 3D environment scans. You provide a raw 3D point cloud dataset, and it outputs a segmented point cloud where different types of objects (like buildings, roads, trees, or vehicles) are clearly labeled. This is particularly useful for professionals working with LiDAR or photogrammetry data who need to understand the composition of a 3D space.
117 stars. No commits in the last 6 months.
Use this if you need to semantically categorize parts of large 3D point clouds, especially when you have limited annotated data.
Not ideal if your primary need is 3D object detection or instance segmentation of individual objects rather than overall scene understanding.
Stars
117
Forks
13
Language
Python
License
MIT
Category
Last pushed
Apr 27, 2023
Commits (30d)
0
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