SelfDeco: Self-Supervised Monocular Depth Completion in Challenging Indoor Environments
Jaehoon Choi Dongki Jung Yonghan Lee Deokhwa Kim Dinesh Manocha Donghwan Lee Jaehoon Choi Dongki Jung Yonghan Lee Deokhwa Kim Dinesh Manocha Donghwan Lee
We present a novel algorithm for self-supervised monocular depth completion. Our approach is based on training a neural network that requires only sparse depth measurements and corresponding monocular video sequences without dense depth labels. Our self-supervised algorithm is designed for challenging indoor environments with textureless regions, glossy and transparent surfaces, moving people, lon...