Semantic Pose Verification for Outdoor Visual Localization with Self-supervised Contrastive Learning

  title={Semantic Pose Verification for Outdoor Visual Localization with Self-supervised Contrastive Learning},
  author={Semih Orhan and Josechu J. Guerrero and Yalin Bastanlar},
Any city-scale visual localization system has to over-come long-term appearance changes, such as varying illumination conditions or seasonal changes between query and database images. Since semantic content is more robust to such changes, we exploit semantic information to improve visual localization. In our scenario, the database consists of gnomonic views generated from panoramic images (e.g. Google Street View) and query images are collected with a standard field-of-view camera at a different… 
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    2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
  • 2021
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