jiajiaandwu Goto Github PK

awesome-deep-visual-odometry

A repository to keep track of Deep Learning based methods for visual odometry (pull requests are always welcome)

cnn_vins

using SuperPoint as visual front to VINS-Mono

deepvo-pytorch

PyTorch Implementation of DeepVO

deep_ekf_vio

denoise-imu-gyro

Convolutional Neural Networks for Denoising Gyroscopes of Low-Cost IMUs(This is a quest for reporoducing the dataset)

d_vins

Merge superpoint、lightglue、MixVPR into VINS-FUSION for loop closure with TensorRT

image-matching

Superpoint and Superglue training and testing code, also some traditional method (SIFT and ORB)

imunet

jiajiaandwu

Config files for my GitHub profile.

orb_slam3

ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM

pyslam

pySLAM contains a monocular Visual Odometry (VO) pipeline in Python. It supports many modern local features based on Deep Learning.

python-vo

A simple python implemented frame-by-frame visual odometry with SuperPoint feature detector and SuperGlue feature matcher.

slambook2

edition 2 of the slambook

slam_lcd-cnn

slam_yolov5

stereo-visual-odometry

Visual Odometry Pipeline using KITTI dataset

superpoint-gtsam-vio

Visual Inertial Odometry using SuperPoint and GTSAM

superpoint-superglue-tensorrt

SuperPoint and SuperGlue with TensorRT. Deploy with C++.

superpoint_slam

SuperPoint + ORB_SLAM2

superslam

(Work in Progress) SuperSLAM: Open Source Framework for Deep Learning based Visual SLAM

viode

VIODE: A Simulated Dataset to Address the Challenges of Visual-Inertial Odometry in Dynamic Environments

yolopoint

Joint Keypoint and Object Detection

yolo_orb_slam3

This is an improved version of ORB-SLAM3 that adds an object detection module implemented with YOLOv5 to achieve SLAM in dynamic environments.