The aim of this paper is to demonstrate that a state of the art feature matcher (LoFTR) can be made more robust to rotations by simply replacing the backbone CNN with a steerable CNN which is equivariant to translations and image rotations. It is experimentally shown that this boost is obtained without reducing performance on ordinary illumination and viewpoint matching sequences.

翻译：本文的目的是要表明,只要用可控的CNN取代主干线CNN,就可以使最先进的地物匹配器(LOFTR)更能适应轮值。 它与翻译和图像旋转等同。 实验性地显示,这种提升的取得并没有降低普通照明和视觉匹配序列的性能。