Deep Depth Estimation from Visual-Inertial SLAM
Kourosh Sartipi,Tien Do,Tong Ke,Khiem Vuong,Stergios I. Roumeliotis,Kourosh Sartipi,Tien Do,Tong Ke,Khiem Vuong,Stergios I. Roumeliotis
This paper addresses the problem of learning to complete a scene's depth from sparse depth points and images of indoor scenes. Specifically, we study the case in which the sparse depth is computed from a visual-inertial simultaneous localization and mapping (VI-SLAM) system. The resulting point cloud has low density, it is noisy, and has nonuniform spatial distribution, as compared to the input fr...
