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Holistic 3D Scene Understanding from a Single Geo-tagged Image

2019-12-19 | |  82 |   46 |   0

Abstract

In this paper we are interested in exploiting geographic priors to help outdoor scene understanding. Towards this goal we propose a holistic approach that reasons jointly about 3D object detection, pose estimation, semantic segmentation as well as depth reconstruction from a single image. Our approach takes advantage of large-scale crowdsourced maps to generate dense geographic, geometric and semantic priors by rendering the 3D world. We demonstrate the effectiveness of our holistic model on the challenging KITTI dataset [13], and show signifificant improvements over the baselines in all metrics and tasks

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