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arXiv · 2010.06944

Relative Depth Estimation as a Ranking Problem

Alican Mertan·Damien Jade Duff·Gozde Unal
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Abstract

We present a formulation of the relative depth estimation from a single image problem, as a ranking problem. By reformulating the problem this way, we were able to utilize literature on the ranking problem, and apply the existing knowledge to achieve better results. To this end, we have introduced a listwise ranking loss borrowed from ranking literature, weighted ListMLE, to the relative depth estimation problem. We have also brought a new metric which considers pixel depth ranking accuracy, on which our method is stronger.

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Alican Mertan, Damien Jade Duff, Gozde Unal. 2020-10-14. Relative Depth Estimation as a Ranking Problem. https://arxiv.org/abs/2010.06944

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