g2o: A General Framework for Graph Optimization

Python binding of SLAM graph optimization framework g2o

MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment

(ICRA 2019) Visual-Odometric On-SE(2) Localization and Mapping

Bundle adjustment demo using Ceres Solver, with customized cost function and local parameterization on SE(3)

SE(2)-Constrained Localization and Mapping by Fusing Odometry and Vision (IEEE Transactions on Cybernetics 2019)

Lightweighted graph optimization (Factor graph) library.

A nonlinear least square(NLLS) solver. Fomulate the NLLS as graph optimization.

Sparse and dynamic camera network calibration with visual odometry

Deploy RT-EDTR with onnx from paddlepaddle framwork and graph cut

Code for paper 'Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware'

DGORL: Distributed Graph Optimization based Relative Localization of Multi-Robot Systems

High Information Mapper (HiMap), successor of the Lead Optimization Mapper (LOMAP)

graph-based optimization INS/GNSS positioning

Implementation of Least Squares Graph Optimization algorithm for graph-based SLAM.

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)

The algorithms for multilevel evaluation of balance in signed directed networks

A curated list of amazingly awesome things regarding Graph Structure Learning.

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.

The algorithm based on the XOR model (Aref et al. 2019) for computing the exact value of frustration index (also called line index of balance)