SPair-71k is a large-scale benchmark dataset for semantic correspondence (semantic keypoint matching) introduced by Min et al. (2019). It contains 70,958 semantically paired images with large intra-class variations in viewpoint and scale and provides accurate, rich annotations intended for evaluating semantic correspondence methods. Annotations include per-image-pair semantic keypoint correspondences, bounding boxes, segmentation masks and metadata about viewpoint/scale variation, truncation and occlusion. The dataset is commonly used as a testbed for semantic keypoint/correspondence and matching algorithms and is distributed with a project page and an arXiv preprint (arXiv:1908.10543). A Hugging Face dataset mirror is also available.
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