{"url":"/dataset/deic-benchmark","name":"DEIC Benchmark","full_name":"Data-Efficient Image Classification Benchmark","description_markdown":"DEIC is a benchmark for measuring the data efficiency of models in the context of image classification.\r\nIt is composed of 6 datasets that contain a small number of training samples per class (i.e., 30 < x < 80).\r\nIt covers multiple image domains (i.e., natural images, fine-grained recognition, medical images, remote sensing, handwriting recognition) and data types (i.e., RGB, grayscale, multi-spectral).","description_withheld":null,"homepage":"https://github.com/cvjena/deic","introduced_date":"2021-08-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/tune-it-or-don-t-use-it-benchmarking-data","title":"Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification","first_author":"Lorenzo Brigato","url":null},"license":{"name":"Custom","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Small Data Image Classification","url":"/task/small-data","datasets_with_task":"/datasets/task/small-data"}],"languages":[],"variants":["CUB-200-2011, 30 samples per class","ImageNet 50 samples per class","ciFAIR-10","EuroSAT 50 samples per class","Data-Efficient Image Classification (DEIC) Benchmark","DEIC Benchmark","ciFAIR-10 50 samples per class"],"data_loaders":[{"repo":"https://github.com/cvjena/deic","url":"https://github.com/cvjena/deic","frameworks":[]}],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/small-data-image-classification-on-deic","task":"Small Data Image Classification","dataset_variant":"DEIC Benchmark","rows":10,"metrics":["Average Balanced Accuracy (across datasets)"],"first_row_in_archive_order":{"model":"Harmonic Networks","paper":"/paper/tune-it-or-don-t-use-it-benchmarking-data","metrics":{"Average Balanced Accuracy (across datasets)":"68.70"},"code_links":[{"title":"cvjena/deic","url":"https://github.com/cvjena/deic"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/small-data-image-classification-on-cifair-10-1","task":"Small Data Image Classification","dataset_variant":"ciFAIR-10 50 samples per class","rows":5,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"ChimeraMix+AutoAugment","paper":"/paper/image-classification-on-small-datasets-via","metrics":{"Accuracy":"70.09"},"code_links":[{"title":"creinders/chimeramix","url":"https://github.com/creinders/chimeramix"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/small-data-image-classification-on-eurosat-50","task":"Small Data Image Classification","dataset_variant":"EuroSAT 50 samples per class","rows":3,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"Harmonic Networks","paper":"/paper/tune-it-or-don-t-use-it-benchmarking-data","metrics":{"Accuracy":"92.09"},"code_links":[{"title":"cvjena/deic","url":"https://github.com/cvjena/deic"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/image-classification-on-small-datasets-via","title":"ChimeraMix: Image Classification on Small Datasets via Masked Feature Mixing","date":"2022-02-23","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":5,"samples_ran":5,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/tune-it-or-don-t-use-it-benchmarking-data","title":"Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification","date":"2021-08-30","rows_on_this_dataset":16,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":1,"samples_harvested":5,"samples_ran":5,"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."}