anshulpaigwar/Frustum-Pointpillars
Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDAR
This project helps autonomous vehicle engineers improve how self-driving cars 'see' their surroundings in 3D. It takes raw data from the car's RGB cameras and LiDAR sensors and precisely identifies objects like pedestrians and cars in 3D space. Autonomous vehicle perception engineers would use this to enhance the car's ability to understand its environment for better decision-making and path planning.
No commits in the last 6 months.
Use this if you are working on autonomous vehicle perception and need to accurately detect 3D objects, especially small ones like pedestrians, using both camera and LiDAR data.
Not ideal if your application doesn't involve autonomous vehicles, 3D object detection, or relies solely on 2D image data without LiDAR.
Stars
61
Forks
15
Language
Python
License
MIT
Category
Last pushed
May 04, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/anshulpaigwar/Frustum-Pointpillars"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
isl-org/Open3D
Open3D: A Modern Library for 3D Data Processing
cvg/Hierarchical-Localization
Visual localization made easy with hloc
gmberton/CosPlace
Official code for CVPR 2022 paper "Rethinking Visual Geo-localization for Large-Scale Applications"
Vincentqyw/image-matching-webui
🤗 image matching webui
cvg/glue-factory
Training library for local feature detection and matching