Visual localization made easy with hloc

Learn OpenCV : C++ and Python Examples

From Coarse to Fine: Robust Hierarchical Localization at Large Scale with HF-Net (https://arxiv.org/abs/1812.03506)

[ICCV 2019] Monocular depth estimation from a single image

A map representation based on 3D segments

Pytorch version of SfmLearner from Tinghui Zhou et al.

Event Vision Library (EVL)

Code for the paper "High Speed and High Dynamic Range Video with an Event Camera" (T-PAMI, 2019).

PyTorch deep learning projects made easy.

LSD-SLAM

A Versatile and Accurate Monocular SLAM

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

(CVPR 2019) Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

Direct Sparse Odometry

OKVIS: Open Keyframe-based Visual-Inertial SLAM.

An Efficient Probabilistic 3D Mapping Framework Based on Octrees. Contains the main OctoMap library, the viewer octovis, and dynamicEDT3D.

A Modular and Multi-Modal Mapping Framework

S-PTAM: Stereo Parallel Tracking and Mapping

The Kalibr visual-inertial calibration toolbox

Intel® RealSense™ SDK

Realtime Edge Based Visual Odometry for a Monocular Camera

g2o: A General Framework for Graph Optimization

Small library with various (visualization) tools in the context of computer vision. To be used together with OpenGL, OpenCV, Eigen and pangolin.

C++ implementation of Lie Groups using Eigen.

This is a general and scalable framework for visual SLAM. It employs "Double Window Optimization" (DWO).

Pangolin is a lightweight portable rapid development library for managing OpenGL display / interaction and abstracting video input.