This video presents the results of SLAM using higher level semantic information. The front end of the algorithm uses VI odometry measurement which accumulate drift. The backend uses the G20 graph SLAM library for correcting this accumulated drift.
Link to code: https://github.com/hridaybavle/semantic_slam.git
Link to paper: https://ieeexplore.ieee.org/document/9045978/
