{"url":"/dataset/cinat-birds-2021","name":"CiNAT-Birds-2021","full_name":"Cross-View iNaturalist Birds 2021","description_markdown":"CiNAT Birds 2021 (Cross-View iNaturalist-2021 Birds) dataset contains ground-level images of bird species along with satellite images associated with the geolocation of the ground-level images. In total, there are 413,959 pairs for training and 14,831 pairs for validation and testing. The ground-level images are of varying sizes while the satellite images are of size 256x256. Additionally, the dataset comes with rich metadata for each image - geolocation, date, observer id, taxonomy.","description_withheld":null,"homepage":"https://github.com/mvrl/BirdSAT","introduced_date":"2023-10-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/birdsat-cross-view-contrastive-masked","title":"BirdSAT: Cross-View Contrastive Masked Autoencoders for Bird Species Classification and Mapping","first_author":"Srikumar Sastry","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Fine-Grained Image Classification","url":"/task/fine-grained-image-classification","datasets_with_task":"/datasets/task/fine-grained-image-classification"},{"name":"Cross-Modal Retrieval","url":"/task/cross-modal-retrieval","datasets_with_task":"/datasets/task/cross-modal-retrieval"}],"languages":[],"variants":["CiNAT-Birds-2021"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}