(video) On Monocular Depth Estimation: (1) MonoDEVS ; (2) Multi-modal Co-training : Antonio M. López

3rd 3D-DLAD @IV’2021 : https://sites.google.com/view/3d-dlad-v3-iv2021/schedule
Abstract : Depth information is essential for on-board perception in autonomous driving. Monocular depth estimation (MDE) is very appealing since it allows for appearance and depth being on direct pixelwise correspondence without further calibration.

In this talk, we present MonoDEVS, our MDE approach to train on virtual-world supervision and real-world SfM self-supervision (thus, on monocular sequences). In addition, we present our recent results on semi-supervised learning (SSL) for object annotation in on-board images. More specifically, we use co-training as SSL approach, assessing the usefulness of MDE as one of the data views for co-training.