g2o: A General Framework for Graph Optimization
-
Updated
May 30, 2024 - C++
g2o: A General Framework for Graph Optimization
Python binding of SLAM graph optimization framework g2o
(ICRA 2019) Visual-Odometric On-SE(2) Localization and Mapping
MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment
SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)
Bundle adjustment demo using Ceres Solver, with customized cost function and local parameterization on SE(3)
Lightweighted graph optimization (Factor graph) library.
Code for paper 'Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware'
Sparse and dynamic camera network calibration with visual odometry
A nonlinear least square(NLLS) solver. Fomulate the NLLS as graph optimization.
DGORL: Distributed Graph Optimization based Relative Localization of Multi-Robot Systems
Deploy RT-EDTR with onnx from paddlepaddle framwork and graph cut
The algorithm based on the UBQP model (Aref et al. 2018) for computing the exact value of frustration index (also called line index of balance)
High Information Mapper (HiMap), successor of the Lead Optimization Mapper (LOMAP)
The algorithms for multilevel evaluation of balance in signed directed networks
Repository of the ECML PKDD 2021 tutorial title 'Machine Learning Meets Internet of Things: From Theory to Practice'
Implementation of Least Squares Graph Optimization algorithm for graph-based SLAM.
my implimentiona and implimentation of visual based SLAM algorithms
GPU implementation of Floyd-Warshall and R-Kleene algorithms to solve the All-Pairs-Shortest-Paths(APSP) problem on Graphs. Code includes random graph generators and benchmarking/plotting scripts.
Add a description, image, and links to the graph-optimization topic page so that developers can more easily learn about it.
To associate your repository with the graph-optimization topic, visit your repo's landing page and select "manage topics."