AmsterTime is a visual place recognition (VPR) benchmark designed to evaluate retrieval and verification under severe domain shift (temporal, viewpoint and camera changes). The dataset contains ~2,500 carefully curated image pairs that match the same scene in Amsterdam: historical archival images (1200+ license-free images from the Amsterdam City Archive) paired with contemporary street-level images sourced from Mapillary. Matches were human-verified and the benchmark supports verification and retrieval evaluations (mean Average Precision (mAP) reported for retrieval). The authors evaluate non-learning, supervised and self-supervised baselines (e.g., ResNet-101 pre-trained on Landmarks) and provide extracted feature sets and dataset releases via a data repository (4TU ResearchData) and a GitHub repo.
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