2021
ADAADepth: Adapting Data Augmentation and Attention for Self-Supervised Monocular Depth Estimation
RA-L 2021
Self-supervised learning of depth has been a highly studied topic of research as it alleviates the requirement of having ground truth annotations for predicting depth. Depth is learnt as an intermediate solution to the task of view synthesis, utilising warped photometric consistency. Although it giv