2019
SGANVO: Unsupervised Deep Visual Odometry and Depth Estimation With Stacked Generative Adversarial Networks
RA-L 2019
Recently end-to-end unsupervised deep learning methods have demonstrated an impressive performance for visual depth and ego-motion estimation tasks. These data-based learning methods do not rely on the same limiting assumptions that geometry-based methods do. The encoder-decoder network has been wid