visual-odometry

OpenVSLAM: A Versatile Visual SLAM Framework

An unsupervised learning framework for depth and ego-motion estimation from monocular videos

LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping

An Invitation to 3D Vision: A Tutorial for Everyone

[CoRL 21'] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo

Unsupervised Scale-consistent Depth Learning from Video (IJCV2021 & NeurIPS 2019)

Robotics with GPU computing

A general framework for map-based visual localization. It contains 1) Map Generation which support traditional features or deeplearning features. 2) Hierarchical-Localizationvisual in visual(points or line) map. 3)Fusion framework with IMU, wheel odom and GPS sensors.

Depth and Flow for Visual Odometry

Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction

This repository is C++ OpenCV implementation of Stereo Odometry

A simple monocular visual odometry (part of vSLAM) by ORB keypoints with initialization, tracking, local map and bundle adjustment. (WARNING: Hi, I'm sorry that this project is tuned for course demo, not for real world applications !!!)

Learning Depth from Monocular Videos using Direct Methods, CVPR 2018

Implementation of ICRA 2019 paper: Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation

A bunch of state estimation algorithms

Visual odometry package based on hardware-accelerated NVIDIA Elbrus library with world class quality and performance.

MATLAB Implementation of Visual Odometry using SOFT algorithm

Efficient monocular visual odometry for ground vehicles on ARM processors

Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency (AAAI 2021)

深度学习和三维视觉相关的论文

RGB-D Encoder SLAM for a Differential-Drive Robot in Dynamic Environments

The official Implementation of "Structure PLP-SLAM: Efficient Sparse Mapping and Localization using Point, Line and Plane for Monocular, RGB-D and Stereo Cameras"

This repository intends to enable autonomous drone delivery with the Intel Aero RTF drone and PX4 autopilot. The code can be executed both on the real drone or simulated on a PC using Gazebo. Its core is a robot operating system (ROS) node, which communicates with the PX4 autopilot through mavros. It uses SVO 2.0 for visual odometry, WhyCon for visual marker localization and Ewok for trajectoy planning with collision avoidance.

EndoSLAM Dataset and an Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner

Simultaneous Visual Odometry, Object Detection, and Instance Segmentation

Ros package for Edge Alignment with Ceres solver

Visual odometry using optical flow and neural networks

Code for T-ITS paper "Unsupervised Learning of Depth, Optical Flow and Pose with Occlusion from 3D Geometry" and for ICRA paper "Unsupervised Learning of Monocular Depth and Ego-Motion Using Multiple Masks".

Implementation of DeepVO (ICRA 2017)