7. [VSLAM] 2020-01-13-Direct Sparse Visual-Inertial Odometry with Stereo Cameras Quantitative evaluation demonstrates that the proposed Stereo VI-DSO is superior to Stereo DSO both in terms of tracking accuracy and robustness. But the result is worse than VINS.
17. [VSLAM] 2020-02-10-Bidirectional Trajectory Computation for Odometer-Aided Visual-Inertial SLAM not only solves the problem of the unobservability of accelerometer bias and extrinsic parameters before the first turning, but also results in more accurate trajectories in comparison with the state-of-the-art approaches.
21. [Semantic] 2020-02-12-Edge Assisted Mobile Semantic Visual SLAM edgeSLAM leverages the state-of-the-art semantic segmentation algorithm to enhance localization and mapping accuracy, and speeds up the computation-intensive SLAM and semantic segmentation algorithms by computation offloading.
33. [VSLAM] 2020-02-16-DeepFactors: Real-Time Probabilistic Dense Monocular SLAM use of a learned compact depth map representation and reformulating three different types of errors: photometric, reprojection and geometric, which we make use of within standard factor graph software. code
39. [VSLAM] 2020-03-02-Dynamic SLAM: The Need For Speedfeature-based, model-free, object-aware dynamic SLAM algorithm that exploits semantic segmentation to allow estimation of motion of rigid objects in a scene without the need to estimate the object poses or have any prior knowledge of their 3D models.
42. [Math] 2020-03-04-Least Squares Optimization: from Theory to Practice a unified methodology to design and develop efficient Least-Squares Optimization algorithms, focusing on the structures and patterns of each specific domain.code