EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner
Published in
(2020)External Links:
TL
TL;DR
A comprehensive endoscopic SLAM dataset consisting of 3D point cloud data for six porcine organs, capsule and standard endoscopy recordings as well as synthetically generated data is introduced and Endo-SfMLearner, an unsupervised monocular depth and pose estimation method that combines residual networks with spatial attention module is propound.