论文标题
相对深度估计作为排名问题
Relative Depth Estimation as a Ranking Problem
论文作者
论文摘要
我们将单个图像问题的相对深度估计值表示为排名问题。通过以这种方式重新解决问题，我们能够利用排名问题的文献，并运用现有知识以获得更好的结果。为此，我们引入了从排名文献（加权ListMle）到相对深度估计问题的列表排名损失。我们还带来了一个新的指标，该指标考虑了像素深度排名精度，我们的方法更强。
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.
