2019
Recurrent Neural Network for (Un-)Supervised Learning of Monocular Video Visual Odometry and Depth
CVPR 2019poster
Deep learning-based, single-view depth estimation methods have recently shown highly promising results. However, such methods ignore one of the most important features for determining depth in the human vision system, which is motion. We propose a learning-based, multi-view dense depth map and odome…