AmsterTime: A Visual Place Recognition Benchmark Dataset for Severe Domain Shift

AmsterTime dataset offers a collection of 2,500 well-curated images matching the same scene from a street view matched to historical archival image data from Amsterdam city. The image pairs capture the same place with different cameras, viewpoints, and appearances. Unlike existing benchmark datasets, AmsterTime is directly crowdsourced in a GIS navigation platform (Mapillary). In turn, all the matching pairs are verified by a human expert to verify the correct matches and evaluate the human competence in the Visual Place Recognition (VPR) task for further references. The properties of the dataset are summarized as:1200+ license-free images from the Amsterdam City Archive, representing urban places in the city of Amsterdam, captured in the past century by many photographers.All archival queries are matched with street view images from Mapillary.All matches are verified by architectural historians and Amsterdam inhabitants.Image pairs are archival and street views capturing the same place with different cameras, time lags, structural changes, occlusion, viewpoint, appearance, and illuminations.The dataset exhibits a domain shift between query and the gallery due to significant difference between scanned archival and street view images.Two sub-tasks are created on the dataset:Verification is a binary classification (auxiliary) task to detect a pair of archival and street-view images of the same place. The verification task for AmsterTime dataset has all of the crowdsourced image pairs as positive labeled, where the same number of negative samples are generated by randomly pairing archival and street-view images summing up to a total of 2,462 pairs in the verification task.Retrieval is the main task corresponding to VPR, in which a given query image is matched with a set of gallery images. For the retrieval task, AmsterTime dataset offers 1231 query images where the leave-one-out set serves as the gallery images for each query.

AmsterTime数据集收录了2500张经过精心甄选的图像集合，这些图像均对应与阿姆斯特丹城市历史档案影像数据匹配的同一街景场景。该图像对以不同相机、拍摄视角与视觉呈现效果捕捉同一地点。与现有基准数据集不同，AmsterTime数据集直接通过地理信息系统（Geographic Information System, GIS）导航平台Mapillary完成众包采集。随后，所有匹配对均经过人类专家核验，以确认匹配准确性，并用于评估视觉地点识别（Visual Place Recognition, VPR）任务中的人类表现，以供后续研究参考。

该数据集的核心属性总结如下：
1. 包含1200余张来自阿姆斯特丹城市档案馆的免授权图像，涵盖过去一个世纪由多位摄影师拍摄的阿姆斯特丹城市各类场所；
2. 所有档案查询图像均与Mapillary平台的街景图像完成匹配；
3. 所有匹配对均由建筑历史学家与阿姆斯特丹本地居民核验确认；
4. 每一组图像对分别为档案影像与街景图像，以不同相机参数、时间跨度、结构变化、遮挡情况、拍摄视角、视觉呈现与光照条件捕捉同一地点；
5. 由于扫描档案影像与街景图像存在显著差异，该数据集的查询集与图库集之间存在明显的领域偏移。

本数据集设置了两项标准子任务：
1. 验证任务（Verification）：这是一项二元分类辅助任务，用于识别属于同一地点的档案影像与街景图像对。AmsterTime数据集的验证任务以全部众包图像对作为正样本，并通过随机配对档案影像与街景图像生成等量负样本，最终验证任务总计包含2462个图像对；
2. 检索任务（Retrieval）：这是对应视觉地点识别的核心任务，即给定一张查询图像，从图库集中匹配出对应的目标图像。针对检索任务，AmsterTime数据集提供了1231张查询图像，且每个查询的图库集均采用留一法构建。