We demonstrate the utility of recurring pattern discovery from a single image for spatial understanding of a 3D scene in terms of (1) vanishing point detection, (2) hypothesizing 3D translation symmetry and (3) counting the number of RP instances in the image. Furthermore, we illustrate the feasibility of leveraging RP discovery output to form a more precise, quantitative text description of the scene. Our quantitative evaluations on a new 1K+ Recurring Pattern (RP) benchmark with diverse variations show that visual perception of recurrence from one single view leads to scene understanding outcomes that are as good as or better than existing supervised methods and/or unsupervised methods that use millions of images.

翻译：我们展示了从单一图像中反复发现的模式对于空间理解三维场景的有用性,即(1) 消失点探测,(2) 假设三维翻译对称,(3) 计算图像中RP实例的数量,此外,我们说明了利用RP发现输出来形成更精确、定量的场景文字描述的可行性。我们对1K+重复模式(RP)新基准的定量评估,其中存在各种差异,表明从一个角度对重复的视觉感知导致对场景结果的理解好于或好于使用数百万图像的现有监督方法和(或)未经监督的方法。