| VO(Feature-base) |
MonoSLAM: realtime single camera SLAM |
Mono-SLAM |
Imperial college |
2007 |
Andrew J. Davison/ Olivier Stasse |
paper |
github |
|
Parallel Tracking and Mapping on a Camera Phone/ S-PTAM: Stereo parallel tracking and mapping |
PTAM/ S-PTAM |
oxford |
2009 |
Georg Klein/ David Murray |
paper |
|
|
REMODE: Probabilistic, monocular dense reconstruction in real time |
REMODE |
ETH |
2014 |
Matia Pizzoli/ Davide Scaramuzza |
|
github |
|
ORB-SLAM: a versatile and accurate monocular SLAM system |
ORB-SLAM |
Zaragoza |
2015 |
Raul Mur-Artal/ Juan D. Tardos |
paper |
|
|
Proslam: Graph SLAM from a programmer's perspective |
pro-SLAM |
|
2018 |
Dominik Schlegel/ Giorgio Grisetti |
paper |
github |
|
OpenVSLAM: A Versatile Visual SLAM Framework |
OpenVSLAM |
|
2019 |
Shinya Sumikura/ Ken Sakurada |
paper |
github |
|
UcoSLAM: Simultaneous Localization and Mapping by Fusion of KeyPoints and Squared Planar Markers |
VO + Marker |
|
2019 |
Rafael Munoz-Salinas/ R. Medina-Carnicer |
paper |
github |
| VO(Direct method) |
DTAM: Dense tracking and mapping in real-time |
DTAM |
Imperial college |
2011 |
Richard Newcombe/ Andrew J. Davison |
paper |
github |
|
LSD-SLAM: Large-scale direct monocular SLAM |
LSD-SLAM |
TUM |
2014 |
Jakob Engel/ Daniel Cremers |
paper |
github |
|
SVO: Fast semi-direct monocular visual odometry |
SVO |
ETH |
2014 |
Christian Forster/ Davide Scaramuzza |
paper |
github |
|
SVO2 |
SVO2 |
|
|
|
|
|
|
Direct sparse odometry |
DSO |
TUM |
2018 |
Jakob Engel/ Daniel Cremers |
|
github |
| VIO |
A multi-state constraint Kalman filter for vision-aided inertial navigation |
MSCKF |
Minnesota |
2007 |
Anastasios I. Mourikis/ Stegios I. Roumeliotis |
paper |
github |
|
Robust vision-aided navigation using sliding-window factor graph |
Sliding window approach |
|
2013 |
Han-pang Chiu/ Rakesh Kumar |
paper |
|
|
Keyframe-based visual–inertial odometry using nonlinear optimization |
Global optimization approach |
ETH |
2015 |
Stefan Leutenegger/ Paul Furgale |
paper |
|
|
IMU preintegration on manifold for efficient visual-inertial maximum-a-posteriori estimation |
IMU Preintegration |
ETH |
2015, 2016 |
Christain Forster/ Davide Scaramuzza |
paper |
|
|
Keyframe-based visual–inertial odometry using nonlinear optimization |
OKVIS |
ETH |
2015 |
Stefan Leutenegger / Paul Furgale |
paper |
github |
|
Simultaneous state initlaization and gyroscope bias calibration in visual inertial aided navigation |
IMU + Camera initialization |
ETH |
2017 |
Jacques Kaiser/ Davide Scaramuzza |
paper |
|
|
Rovio/ Roviloi/ Maplab |
Rovio/ Roviloi/ Maplab |
ETH |
2015/ 2017 |
Michael Bloesch/ Roland Siegwart |
paper |
github |
|
Vins-mono: A robust and versatile monocular visual-inertial state estimator / A General Optimization-based Framework for global pose estimation with multiple sensors |
VINS-Mono/ VINS-Fusion |
HKUST |
2018/ 2019 |
Tong Qin/ Shaojie Shen |
paper |
github, github |
|
Robust stereo visual inertial odometry for fast autonomous flight |
Stereo + IMU |
Kumar lab (penn) |
2018 |
Ke Sun/ Vijay Kumar |
paper |
|
|
ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM |
ORB-SLAM3 |
Zaragoza |
|
Carlos Campos/ Juan D. Tardós |
paper |
github |
| Deep-Learning |
CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction |
CNN SLAM |
|
2017 |
Keisuke Tateno/ Nassir Navab |
paper |
|
|
Superpoint: Self-supervised interest point detection and description |
SuperPoint |
|
2018 |
Daniel DeTone/ Andrew Rabinovich |
paper |
|
|
Lift: Learned invariant feature transform |
LIFT |
|
2016 |
Kwang Moo Yi/ Fascal Fua |
paper |
|
|
PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization |
PoseNet |
|
2015 |
Alex Kendal / Roberto Cipolla |
paper |
|
|
UnDeepVO: Monocular Visual Odometry through Unsupervised Deep |
UnDeepVO |
|
2018 |
Ruihao Li/ Dongbing Gu |
paper |
|
|
DSAC - Differentiable RANSAC for Camera Localization |
DSAC |
|
2017 |
Eric Brachmann/ Carsten Rother |
paper |
|
