Datasets › Met
Met
The Met dataset is a large-scale dataset for Instance-Level Recognition (ILR) in the artwork domain. It relies on the open access collection from the Metropolitan Museum of Art (The Met) in New York to form the training set, which consists of about 400k images from more than 224k classes, with artworks of world-level geographic coverage and chronological periods dating back to the Paleolithic period. Each museum exhibit corresponds to a unique artwork, and defines its own class. The training set exhibits a long-tail distribution with more than half of the classes represented by a single image, making it a special case of few-shot learning.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 11 papers for it but never published that list.
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
No task tagged in the archive.
License archive 2025-07-28
Unknown
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- Met
1 variant name, as the archive lists them.
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