{"url":"/task/few-shot-object-counting-and-detection","name":"Few-shot Object Counting and Detection","slug":"few-shot-object-counting-and-detection","description_markdown":"Few-shot Object Counting and Detection aims to **count and detect** instances of objects of the same class as given exemplars within a single image, using only up to three exemplars from the original FSC147. This task is especially challenging but crucial when large datasets are unavailable. Methods for this task must output a **single set of bounding boxes**, from which the final count is derived based on the number of detected boxes.","categories":[{"name":"Computer Vision","url":"/area/computer-vision"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":4,"papers_with_code":4,"benchmarks":2,"benchmark_tables_in_archive":2,"benchmark_tables_shown":2,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":1,"subtasks":0,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/few-shot-object-counting-and-detection-on","slug":"few-shot-object-counting-and-detection-on","dataset":"FSC147","dataset_url":"/dataset/fsc147","rows_in_archive":4,"metrics":["MAE(test)","RMSE(test)","AP50(test)","AP(test)"],"first_row_in_archive_order":{"model":"GeCo","paper_title":"A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation","paper_url":"/paper/a-novel-unified-architecture-for-low-shot","paper_date":"2024-09-27","arxiv_id":"2409.18686","code_links":[{"title":"jerpelhan/GeCo","url":"https://github.com/jerpelhan/GeCo"}],"syntology":null}},{"leaderboard":"/sota/few-shot-object-counting-and-detection-on-1","slug":"few-shot-object-counting-and-detection-on-1","dataset":"Zero Shot Counting on FSC147","dataset_url":null,"rows_in_archive":1,"metrics":["MAE(test)"],"first_row_in_archive_order":{"model":"SAVE","paper_title":"SAVE: Self-Attention on Visual Embedding for Zero-Shot Generic Object Counting","paper_url":"/paper/save-self-attention-on-visual-embedding-for","paper_date":"2025-02-10","arxiv_id":null,"code_links":[{"title":"AhmedZgaren/Save","url":"https://github.com/AhmedZgaren/Save"}],"syntology":null}}],"datasets":[{"url":"/dataset/fsc147","name":"FSC147","full_name":"","num_papers_in_archive":58}],"subtasks":[],"parent_tasks":[{"url":"/task/object-counting","name":"Object Counting"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":4,"of":4,"tagged_in_all":4,"items":[{"url":"/paper/a-novel-unified-architecture-for-low-shot","title":"A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation","date":"2024-09-27","arxiv_id":"2409.18686","repositories_listed":1,"syntology":null},{"url":"/paper/dave-a-detect-and-verify-paradigm-for-low","title":"DAVE -- A Detect-and-Verify Paradigm for Low-Shot Counting","date":"2024-04-25","arxiv_id":"2404.16622","repositories_listed":1,"syntology":{"n":18,"n_ran":16,"n_unverified":2,"n_pointer_only":0}},{"url":"/paper/point-segment-and-count-a-generalized-1","title":"Point Segment and Count: A Generalized Framework for Object Counting","date":"2024-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/few-shot-object-counting-and-detection","title":"Few-shot Object Counting and Detection","date":"2022-07-22","arxiv_id":"2207.10988","repositories_listed":1,"syntology":{"n":4,"n_ran":0,"n_unverified":4,"n_pointer_only":0}}],"syntology_records":2,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}