g2o: A General Framework for Graph Optimization
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Updated
Aug 31, 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)
Repository of the ECML PKDD 2021 tutorial title 'Machine Learning Meets Internet of Things: From Theory to Practice'
The algorithms for multilevel evaluation of balance in signed directed networks
Optimization of graph-based machine learning models using advanced algorithms and techniques.
Implementation of Least Squares Graph Optimization algorithm for graph-based SLAM.
Source Code for 'Entropy Regularization for Unsupervised Clustering with Adaptive Neighbors' (PR)
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