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.

A basic implementation(not official code) of AVP-SLAM(IROS 2020) in simulation. https://arxiv.org/abs/2007.01813

orb-slam2 with semantic label

SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation

Implementation of IROS20 paper - "Semantic Graph Based Place Recognition for 3D Point Clouds"

Bayesian Spatial Kernel Smoothing for Scalable Dense Semantic Mapping

Repository for the paper "Extending Maps with Semantic and Contextual Object Information for Robot Navigation: a Learning-Based Framework using Visual and Depth Cues"

Semantic DSP Map in paper "Particle-based Instance-aware Semantic Occupancy Mapping in Dynamic Environments"

Scene Flow Propagation for Semantic Mapping and Object Discovery in Dynamic Street Scenes

Autonomous Exploration, Construction and Update of Semantic Map in real-time

[IROS2024]DHP-Mapping: A Dense Panoptic Mapping System with Hierarchical World Representation and Label Optimization Techniques

Implementation of Volume-DROID

Multi-Task Learning for Scalable and Dense Multi-Layer Bayesian Map Inference

Efficient and Robust Semantic Mapping for Indoor Environments

Object-based CNN

A SEmantic Modeling machIne to build Knowledge Graphs with Graph Neural Networks

This is a robotic package for an algorithm for visual teach and repeat

InEKF Localization and Semantic Mapping on the KITTI Dataset

Multi-Robot Exploration, Mapping and Navigation using ros2

Learning Aided Semantic Bayesian Kernel Inference for 3D Semantic Global Mapping