2018
Unsupervised Learning of Depth and Ego-Motion From Monocular Video Using 3D Geometric Constraints
CVPR 2018poster
We present a novel approach for unsupervised learning of depth and ego-motion from monocular video. Unsupervised learning removes the need for separate supervisory signals (depth or ego-motion ground truth, or multi-view video). Prior work in unsupervised depth learning uses pixel-wise or gradient-…