Dense depth in crowded dynamic scenes using sparse depth and monocular color images

Dense depth in crowded dynamic scenes using sparse depth and monocular color images

DnD: Dense Depth Estimation in Crowded Dynamic Indoor Scenes

arXiv paper abstract https://arxiv.org/abs/2108.05615v1

arXiv PDF paper https://arxiv.org/pdf/2108.05615v1.pdf

We present a novel approach for estimating depth from a monocular camera as it moves through complex and crowded indoor environments, e.g., a department store or a metro station.

... approach predicts absolute scale depth maps over the entire scene consisting of a static background and multiple moving people, by training on dynamic scenes.

... training framework without requiring depths produced from depth sensing devices.

... network leverages RGB images and sparse depth maps generated from traditional 3D reconstruction methods to estimate dense depth maps.

... approach offers consistent improvements over recent depth estimation methods on the NAVERLABS dataset, which includes complex and crowded scenes.

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