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Search results with tag "Digging into self supervised monocular depth estimation"
Digging Into Self-Supervised Monocular Depth Estimation
openaccess.thecvf.comWe first review the key ideas behind self-supervised train-ing for monocular depth estimation, and then describe our depth estimation network and joint training loss. 3.1. SelfSupervised Training Self-supervised depth estimation frames the learning problem as one of novel view-synthesis, by training a net-
Digging Into Self-Supervised Monocular Depth Estimation
arxiv.orgauto-masking loss to ignore training pixels that violate cam-era motion assumptions. We demonstrate the effectiveness of each component in isolation, and show high quality, state-of-the-art results on the KITTI benchmark. 1. Introduction We seek to automatically infer a dense depth image from a single color input image. Estimating absolute, or even