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pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
:taxi: Fast and robust clustering of point clouds generated with a Velodyne sensor.
Ground Segmentation from Lidar Point Clouds
Real-Time 3D Semantic Reconstruction from 2D data
Real time semantic slam in ROS with a hand held RGB-D camera
The LiDAR segmenters library, for segmentation-based detection.
Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗
ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite