Estimating probability distributions which describe where an object is likely to be from camera data is a task with many applications. In this work we describe properties which we argue such methods should conform to. We also design a method which conform to these properties. In our experiments we show that our method produces uncertainties which correlate well with empirical errors. We also show that the mode of the predicted distribution outperform our regression baselines. The code for our implementation is available online.

翻译：从相机数据中估计描述物体可能位置的概率分布是一项具有众多应用的任务。本文阐述了我们认为此类方法应遵循的性质，并设计了一种符合这些性质的方法。实验表明，我们的方法产生的置信度与经验误差具有良好相关性，同时预测分布的模态优于回归基线方法。相关实现代码已在网上公开。