Semi-Supervised Learning with Mutual Distillation for Monocular Depth Estimation
Jongbeom Baek,Gyeongnyeon Kim,Seungryong Kim,Jongbeom Baek,Gyeongnyeon Kim,Seungryong Kim
We propose a semi-supervised learning framework for monocular depth estimation. Compared to existing semi-supervised learning methods, which inherit limitations of both sparse supervised and unsupervised loss functions, we achieve the complementary advantages of both loss functions, by building two separate network branches for each loss and distilling each other through the mutual distillation lo...
