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    README.md

    Visual Odometry(VO)-SLAM-Review

    SLAM is mainly divided into two parts: the front end and the back end. The front end is the visual odometer (VO), which roughly estimates the motion of the camera based on the information of adjacent images and provides a good initial value for the back end.The implementation methods of VO can be divided into two categories according to whether features are extracted or not: feature point-based methods, and direct methods without feature points. VO based on feature points is stable and insensitive to illumination and dynamic objects

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    github:https://github.com/MichaelBeechan

    CSDN:https://blog.csdn.net/u011344545

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    SALM review paper download:

    https://download.csdn.net/download/u011344545/10850261

    1、Visual Odometry or VSLAM

    2、Visual Inertial Odometry or VIO-SLAM

    3、Based CNN(Net VO or Net VSLAM)

    4、Lidar Visual odometry or Lidar SLAM

    5、Semanitc SLAM

    6、Datasets

    7、Libraries

    OF-VO:Robust and Efficient Stereo Visual Odometry Using Points and Feature Optical Flow

    Code:https://github.com/MichaelBeechan/MyStereoLibviso2

    SLAMBook

    Paper:14 Lectures on Visual SLAM: From Theory to Practice,

    Code:https://github.com/gaoxiang12/slambook

    SLAMBook2

    Code:https://github.com/gaoxiang12/slambook2

    SVO: Fast Semi-Direct Monocular Visual Odometry

    Paper:http://rpg.ifi.uzh.ch/docs/ICRA14_Forster.pdf

    Video: http://youtu.be/2YnIMfw6bJY

    Code:https://github.com/uzh-rpg/rpg_svo

    Robust Odometry Estimation for RGB-D Cameras

    Real-Time Visual Odometry from Dense RGB-D Images

    Paper:http://www.cs.nuim.ie/research/vision/data/icra2013/Whelan13icra.pdf

    Code:https://github.com/tum-vision/dvo

    Parallel Tracking and Mapping for Small AR Workspaces

    Paper:https://cse.sc.edu/~yiannisr/774/2015/ptam.pdf

    http://www.robots.ox.ac.uk/ActiveVision/Papers/klein_murray_ismar2007/klein_murray_ismar2007.pdf

    Code:https://github.com/Oxford-PTAM/PTAM-GPL

    ORBSLAM

    Code3:https://github.com/MichaelBeechan/ORBSLAM3

    Paper3:ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM:https://arxiv.org/pdf/2007.11898.pdf

    Code2:https://github.com/raulmur/ORB_SLAM2

    Paper2:ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras:https://arxiv.org/pdf/1610.06475.pdf

    Code1:https://github.com/raulmur/ORB_SLAM

    Paper1:ORB-SLAM: A Versatile and Accurate Monocular SLAM System:https://arxiv.org/pdf/1502.00956.pdf

    A ROS Implementation of the Mono-Slam Algorithm

    Paper:https://www.researchgate.net/publication/269200654_A_ROS_Implementation_of_the_Mono-Slam_Algorithm

    Code:https://github.com/rrg-polito/mono-slam

    DTAM: Dense tracking and mapping in real-time

    Paper:https://ieeexplore.ieee.org/document/6126513

    Code:https://github.com/anuranbaka/OpenDTAM

    LSD-SLAM: Large-Scale Direct Monocular SLAM

    Paper:http://pdfs.semanticscholar.org/c13c/b6dfd26a1b545d50d05b52c99eb87b1c82b2.pdf

    https://vision.in.tum.de/research/vslam/lsdslam

    Code:https://github.com/tum-vision/lsd_slam

    RGBD-Odometry (Visual Odometry based RGB-D images)

    Real-Time Visual Odometry from Dense RGB-D Images

    Code:https://github.com/tzutalin/OpenCV-RgbdOdometry

    Paper:http://www.computer.org/csdl/proceedings/iccvw/2011/0063/00/06130321.pdf

    Py-MVO: Monocular Visual Odometry using Python

    Code:https://github.com/Transportation-Inspection/visual_odometry

    Video:https://www.youtube.com/watch?v=E8JK19TmTL4&feature=youtu.be

    Stereo-Odometry-SOFT

    MATLAB Implementation of Visual Odometry using SOFT algorithm

    Code:https://github.com/Mayankm96/Stereo-Odometry-SOFT

    Paper:https://ieeexplore.ieee.org/document/7324219

    GF_ORB_SLAM:Good Feature Matching: Towards Accurate, Robust VO/VSLAM with Low Latency

    Paper:https://arxiv.org/pdf/2001.00714.pdf

    Code:https://github.com/ivalab/GF_ORB_SLAM

    monoVO-python

    Code1:https://github.com/uoip/monoVO-pythone:https://github.com/uoip/monoVO-python

    Code2:https://github.com/yueying/LearningVO

    DVO:Robust Odometry Estimation for RGB-D Cameras

    Code:https://github.com/tum-vision/dvo

    https://vision.in.tum.de/data/software/dvo

    Paper:https://www.researchgate.net/publication/221430091_Real-time_visual_odometry_from_dense_RGB-D_images

    Dense Visual Odometry and SLAM (dvo_slam)

    Code:https://github.com/tum-vision/dvo_slam

    https://vision.in.tum.de/data/software/dvo

    Paper:https://www.researchgate.net/publication/261353146_Dense_visual_SLAM_for_RGB-D_cameras

    REVO:Robust Edge-based Visual Odometry

    Combining Edge Images and Depth Maps for Robust Visual Odometry

    Robust Edge-based Visual Odometry using Machine-Learned Edges

    Code:https://github.com/fabianschenk/REVO

    Paper:https://graz.pure.elsevier.com/

    xivo

    X Inertial-aided Visual Odometry

    Code:https://github.com/ucla-vision/xivo

    Paper:XIVO: X Inertial-aided Visual Odometry and Sparse Mapping

    PaoPaoRobot

    Code:https://github.com/PaoPaoRobot

    ygz-slam

    Code:https://github.com/PaoPaoRobot/ygz-slam

    https://github.com/gaoxiang12/ygz-stereo-inertial

    https://github.com/gaoxiang12/ORB-YGZ-SLAM

    https://www.ctolib.com/generalized-intelligence-GAAS.html#5-ygz-slam

    RTAB MAP

    Online Global Loop Closure Detection for Large-Scale Multi-Session Graph-Based SLAM, 2014 Appearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation, 2013

    MYNT-EYE

    Code:https://github.com/slightech

    Kintinuous

    Real-time Large Scale Dense RGB-D SLAM with Volumetric Fusion

    Deformation-based Loop Closure for Large Scale Dense RGB-D SLAM

    Robust Real-Time Visual Odometry for Dense RGB-D Mapping

    Kintinuous: Spatially Extended KinectFusion

    A method and system for mapping an environment

    Code:https://github.com/mp3guy/Kintinuous

    ElasticFusion

    ElasticFusion: Dense SLAM Without A Pose Graph

    ElasticFusion: Real-Time Dense SLAM and Light Source Estimation

    Paper:http://www.thomaswhelan.ie/Whelan16ijrr.pdf http://thomaswhelan.ie/Whelan15rss.pdf

    Code:https://github.com/mp3guy/ElasticFusion

    Co-Fusion:Real-time Segmentation, Tracking and Fusion of Multiple Objects

    Paper:http://visual.cs.ucl.ac.uk/pubs/cofusion/index.html

    R-VIO:Robocentric Visual-Inertial Odometry

    (Kimera-VIO is a Visual Inertial Odometry pipeline for accurate State Estimation from Stereo + IMU data.)

    Code:https://github.com/rpng/R-VIO

    Paper:https://arxiv.org/abs/1805.04031

    Kimera-VIO: Open-Source Visual Inertial Odometry

    Code:https://github.com/MIT-SPARK/Kimera-VIO

    Paper:https://arxiv.org/abs/1910.02490

    Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping

    ADVIO: An Authentic Dataset for Visual-Inertial Odometry

    Code:https://github.com/AaltoVision/ADVIO

    Paper:https://arxiv.org/abs/1807.09828

    Data:https://zenodo.org/record/1476931#.XgCvYVIza00

    MSCKF_VIO:Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight

    Paper:https://arxiv.org/abs/1712.00036

    Code:https://github.com/KumarRobotics/msckf_vio

    Kimera-VIO: Open-Source Visual Inertial Odometry

    Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping

    Code:https://github.com/MIT-SPARK/Kimera-VIO

    Paper:https://arxiv.org/abs/1910.02490

    LIBVISO2: C++ Library for Visual Odometry 2

    Paper:http://www.cvlibs.net/software/libviso/

    Code:https://github.com/srv/viso2

    Stereo Visual SLAM for Mobile Robots Navigation

    A constant-time SLAM back-end in the continuum between global mapping and submapping: application to visual stereo SLAM

    Paper:http://mapir.uma.es/famoreno/papers/thesis/FAMD_thesis.pdf

    Code:https://github.com/famoreno/stereo-vo

    Combining Edge Images and Depth Maps for Robust Visual Odometry

    Robust Edge-based Visual Odometry using Machine-Learned Edges(REVO)

    Paper:https://graz.pure.elsevier.com/

    Code:https://github.com/fabianschenk/REVO

    HKUST Aerial Robotics Group

    VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator

    Paper:https://arxiv.org/pdf/1708.03852.pdf

    Code:https://github.com/HKUST-Aerial-Robotics/VINS-Mono

    VINS-Fusion:Online Temporal Calibration for Monocular Visual-Inertial Systems

    Paper:https://arxiv.org/pdf/1808.00692.pdf

    Code:https://github.com/HKUST-Aerial-Robotics/VINS-Fusion

    Monocular Visual-Inertial State Estimation for Mobile Augmented Reality

    Paper:https://ieeexplore.ieee.org/document/8115400

    Code:https://github.com/HKUST-Aerial-Robotics/VINS-Mobile

    Computer Vision Group TUM Department of Informatics Technical University of Munich

    DSO: Direct Sparse Odometry

    Code:https://github.com/JingeTu/StereoDSO

    Visual-Inertial DSOhttps://vision.in.tum.de/research/vslam/vi-dso

    DVSO:https://vision.in.tum.de/research/vslam/dvso

    DSO with Loop-closure and Sim(3) pose graph optimization:https://vision.in.tum.de/research/vslam/ldso

    Stereo odometry based on careful feature selection and tracking

    Paper:https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7324219

    Code:https://github.com/Mayankm96/Stereo-Odometry-SOFT

    OKVIS: Open Keyframe-based Visual-Inertial SLAM

    Code:https://github.com/gaoxiang12/okvis

    Trifo-VIO: Robust and Efficient Stereo Visual Inertial Odometry using Points and Lines

    Paper:https://arxiv.org/pdf/1803.02403.pdf

    Code:https://github.com/UMiNS/Trifocal-tensor-VIO

    PL-VIO: Tightly-Coupled Monocular Visual–Inertial Odometry Using Point and Line Features

    Paper:https://www.mdpi.com/1424-8220/18/4/1159/html

    Overview of visual inertial navigation

    A Review of Visual-Inertial Simultaneous Localization and Mapping from Filtering-Based and Optimization-Based Perspectives:

    https://ieeexplore.ieee.org/document/5423178

    https://www.mdpi.com/2218-6581/7/3/45

    VINet: Visual-Inertial Odometry as a Sequence-to-Sequence Learning Problem

    Paper:https://arxiv.org/abs/1701.08376

    Code:https://github.com/HTLife/VINet

    DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networks

    Code:https://github.com/ildoonet/deepvo

    https://github.com/sladebot/deepvo

    https://github.com/themightyoarfish/deepVO

    https://github.com/fshamshirdar/DeepVO (pytorch)

    Paper:http://www.cs.ox.ac.uk/files/9026/DeepVO.pdf

    UnDeepVO: Implementation of Monocular Visual Odometry through Unsupervised Deep Learning

    Code:https://github.com/drmaj/UnDeepVO

    Paper:https://arxiv.org/pdf/1709.06841.pdf

    SfM-Net: SfM-Net: Learning of Structure and Motion from Video

    Code: https://github.com/waxz/sfm_net

    Paper: https://arxiv.org/pdf/1704.07804v1.pdf

    CNN-SLAM: CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction

    Code: https://github.com/iitmcvg/CNN_SLAM

    Paper:https://arxiv.org/pdf/1704.03489.pdf

    PoseNet: Posenet: A convolutional network for real-time 6-dof camera relocalization(ICCV2015)

    Code:https://github.com/alexgkendall/caffe-posenet or https://github.com/kentsommer/tensorflow-posenet

    Paper:https://arxiv.org/pdf/1505.07427.pdf or https://arxiv.org/pdf/1509.05909.pdf

    VidLoc: VidLoc: 6-doF video-clip relocalization

    Code: https://github.com/futurely/deep-camera-relocalization

    Paper: https://arxiv.org/pdf/1702.06521.pdf

    NetVLAD: NetVLAD: CNN architecture for weakly supervised place recognition(CVPR2016)

    Code: https://github.com/Relja/netvlad (Matlab) or https://github.com/lyakaap/NetVLAD-pytorch

    Paper: https://arxiv.org/pdf/1511.07247.pdf

    DeMoN: Depth and Motion Network for Learning Monocular Stereo(CVPR2017)

    Code: https://github.com/lmb-freiburg/demon

    Paper: https://arxiv.org/pdf/1612.02401v2.pdf

    Learned Stereo Machine

    Code: https://github.com/akar43/lsm

    Paper: https://arxiv.org/pdf/1708.05375.pdf

    SfMLearner: Unsupervised Learning of Depth and Ego-Motion from Video

    Code: https://github.com/tinghuiz/SfMLearner

    Paper: https://arxiv.org/pdf/1704.07813.pdf

    Toward Geometric Deep SLAM

    Code: UNopen(https://github.com/mtrasobaresb)

    Paper: https://arxiv.org/pdf/1707.07410v1.pdf

    Neural SLAM : Learning to Explore with External Memory

    Code: UNopen

    Paper: https://arxiv.org/pdf/1706.09520.pdf

    PoseConvGRU: A Monocular Approach for Visual Ego-motion Estimation by Learning(2019)

    Code: UNopen

    Paper: https://arxiv.org/pdf/1906.08095.pdf

    Semi-Dense 3D Semantic Mapping from Monocular SLAM(2016)

    Code: UNopen

    Paper: https://arxiv.org/pdf/1611.04144.pdf

    Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era(2019)

    Paper: https://arxiv.org/pdf/1906.06543.pdf

    DeepMVS: DeepMVS: Learning Multi-view Stereopsis(CVPR2018)

    Code: https://github.com/phuang17/DeepMVS

    Paper: https://phuang17.github.io/DeepMVS/index.html

    Paper: https://arxiv.org/pdf/1804.00650.pdf

    MVSNet: Mvsnet: Depth inference for unstructured multi-view stereo(ECCV2018)

    Code1: https://github.com/YoYo000/MVSNet

    Code2: https://github.com/YoYo000/BlendedMVS

    Paper: https://arxiv.org/pdf/1804.02505.pdf

    PointMVSNet:Point-based Multi-view Stereo Network

    Code: https://github.com/callmeray/PointMVSNet

    Paper: https://arxiv.org/pdf/1908.04422.pdf

    Recurrent MVSNet: Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference(CVPR2019)

    Code: https://github.com/YoYo000/MVSNet

    Paper: https://arxiv.org/pdf/1902.10556.pdf

    (ESP-VO) End-to-End, Sequence-to-Sequence Probabilistic Visual Odometry through Deep Neural Networks

    Code: https://github.com/espnet/espnet

    https://www.seas.upenn.edu/~meam620/slides/kinematicsI.pdf

    Lidar Visual odometry

    Lidar-Monocular Visual Odometry

    Code:https://github.com/johannes-graeter/limo

    Paper:https://arxiv.org/pdf/1807.07524.pdf

    RGBD and LIDAR

    CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description

    Paper:https://arxiv.org/ftp/arxiv/papers/2001/2001.01354.pdf

    Code:https://github.com/SRainGit/CAE-LO

    Other open source projects

    DynaSLAM A SLAM system robust in dynamic environments for monocular, stereo and RGB-D setups

    openvslam A Versatile Visual SLAM Framework

    cartographer

    Code:https://github.com/googlecartographer/cartographer

    Paper:https://google-cartographer.readthedocs.io/en/latest/

    A-LOAM(Advanced implementation of LOAM)

    LOAM: Lidar Odometry and Mapping in Real-time

    Code1:https://github.com/HKUST-Aerial-Robotics/A-LOAM

    Code2:https://github.com/cuitaixiang/LOAM_NOTED

    Paper:http://roboticsproceedings.org/rss10/p07.pdf

    SemanticFusion: Dense 3D semantic mapping with convolutional neural networks

    Code: https://github.com/seaun163/semanticfusion

    Paper: https://arxiv.org/pdf/1609.05130v2.pdf

    ORB_SLAM2_SSD_Semantic

    Code:https://github.com/Ewenwan/ORB_SLAM2_SSD_Semantic

    Visual Semantic SLAM with Landmarks for Large-Scale Outdoor Environment

    Paper:https://arxiv.org/pdf/2001.01028.pdf

    Code:https://github.com/1989Ryan/Semantic_SLAM/

    Datasets

    Libraries

    Basic vision and trasformation libraries

    Thread-safe queue libraries

    Loop detection

    Graph Optimization

    Map library

    Tools

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