{"url":"/dataset/pattercom","name":"PatternCom","full_name":null,"description_markdown":"PatternCom is a composed image retrieval benchmark based on PatternNet. PatternNet is a large-scale high-resolution remote sensing image retrieval dataset. There are 38 classes and each class has 800 images of size 256×256 pixels. In PatternCom, we select some classes to be depicted in query images, and add a query text that defines an attribute relevant to that class. For instance, query images of “swimming pools” are combined with text queries defining “shape” as “rectangular”, “oval”, and “kidney-shaped”. In total, PatternCom includes six attributes consisted of up to four different classes each. Each attribute can be associated with two to five values per class. The number of positives ranges from 2 to 1345 and there are more than 21k queries in total.","description_withheld":null,"homepage":"","introduced_date":"2024-05-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/composed-image-retrieval-for-remote-sensing","title":"Composed Image Retrieval for Remote Sensing","first_author":"Bill Psomas","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Composed Image Retrieval (CoIR)","url":"/task/composed-image-retrieval","datasets_with_task":"/datasets/task/composed-image-retrieval"},{"name":"Zero-Shot Composed Image Retrieval (ZS-CIR)","url":"/task/zero-shot-composed-image-retrieval-zs-cir","datasets_with_task":"/datasets/task/zero-shot-composed-image-retrieval-zs-cir"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["PatternCom"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/zero-shot-composed-image-retrieval-zs-cir-on-10","task":"Zero-Shot Composed Image Retrieval (ZS-CIR)","dataset_variant":"PatternCom","rows":2,"metrics":["mAP"],"first_row_in_archive_order":{"model":"WeiCom (RemoteCLIP)","paper":"/paper/composed-image-retrieval-for-remote-sensing","metrics":{"mAP":"30.19"},"code_links":[{"title":"billpsomas/rscir","url":"https://github.com/billpsomas/rscir"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/composed-image-retrieval-for-remote-sensing","title":"Composed Image Retrieval for Remote Sensing","date":"2024-05-24","rows_on_this_dataset":2,"code_links":1,"syntology":null}],"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."}