Semantic Segmentation in the Task of Long-Term Visual Localization

In this paper, it is discussed the problem of long-term visual localization with a using of the Aachen Day-Night dataset. Our experiments confirmed that carefully fine-tuning parameters of the Hierarchical Localization method can lead to enhance the visual localization accuracy. Next, our experiments show that it is possible to find an image's area that does not add any valuable information in long-term visual localization and can be removed without losing the localization accuracy. The approach of using the method of semantic segmentation for preprocessing helped to achieve comparable state-of-the-art results in the Aachen Day-Night dataset.