g2o: A General Framework for Graph Optimization
-
Updated
Mar 2, 2026 - C++
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.
Deploy RT-EDTR with onnx from paddlepaddle framwork and graph cut
Sparse and dynamic camera network calibration with visual odometry
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)
Implementation of Least Squares Graph Optimization algorithm for graph-based SLAM.
The algorithms for multilevel evaluation of balance in signed directed networks
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 UBQP model (Aref et al. 2018) for computing the exact value of frustration index (also called line index of balance)
A curated list of amazingly awesome things regarding Graph Structure Learning.
Symbolic shape inference for ONNX
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."