This work presents an analysis of the efficiency of image augmentations for the face recognition problem from limited data. We considered basic manipulations, generative methods, and their combinations for augmentations. Our results show that augmentations, in general, can considerably improve the quality of face recognition systems and the combination of generative and basic approaches performs better than the other tested techniques.

翻译：这项工作从有限的数据中分析了面部识别问题的图像放大效率。 我们考虑了基本操作、基因组化方法及其组合的增强。 我们的结果表明,总体而言,增强可以大大改善面部识别系统的质量以及基因组化和基本方法的结合效果优于其他测试技术。