Unsupervised Domain Adaptation for Depth Prediction from Images
Unsupervised Domain Adaptation for Depth Prediction from Images
State-of-the-art approaches to infer dense depth measurements from images rely on CNNs trained end-to-end on a vast amount of data. However, these approaches suffer a drastic drop in accuracy when dealing with environments much different in appearance and/or context from those observed at training time. This domain shift issue is …