{"url":"/dataset/artaxor","name":"Artaxor","full_name":null,"description_markdown":"Click to add a brief description of the dataset (Markdown and LaTeX enabled).\r\n\r\nProvide:\r\n\r\n* a high-level explanation of the dataset characteristics\r\n* explain motivations and summary of its content\r\n* potential use cases of the dataset","description_withheld":null,"homepage":"","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Cross-Domain Few-Shot Object Detection","url":"/task/cross-domain-few-shot-object-detection","datasets_with_task":"/datasets/task/cross-domain-few-shot-object-detection"}],"languages":[],"variants":["Artaxor"],"data_loaders":[],"num_papers_in_archive":12,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/cross-domain-few-shot-object-detection-on","task":"Cross-Domain Few-Shot Object Detection","dataset_variant":"Artaxor","rows":16,"metrics":[" mAP"],"first_row_in_archive_order":{"model":"ETS","paper":"/paper/enhance-then-search-an-augmentation-search","metrics":{" mAP":"71.2"},"code_links":[{"title":"jaychempan/ETS","url":"https://github.com/jaychempan/ETS"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/no-time-to-train-training-free-reference","title":"No time to train! Training-Free Reference-Based Instance Segmentation","date":"2025-07-03","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/cdformer-cross-domain-few-shot-object","title":"CDFormer: Cross-Domain Few-Shot Object Detection Transformer Against Feature Confusion","date":"2025-05-02","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/enhance-then-search-an-augmentation-search","title":"Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object Detection","date":"2025-04-06","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/balanced-id-ood-tradeoff-transfer-makes-query","title":"Balanced ID-OOD tradeoff transfer makes query based detectors good few shot learners","date":"2024-05-23","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/cross-domain-few-shot-object-detection-via","title":"Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector","date":"2024-02-05","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":9,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/detect-every-thing-with-few-examples","title":"Detect Everything with Few Examples","date":"2023-09-22","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":20,"samples_ran":15,"samples_unverified":5,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/exploring-plain-vision-transformer-backbones","title":"Exploring Plain Vision Transformer Backbones for Object Detection","date":"2022-03-30","rows_on_this_dataset":1,"code_links":11,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":1,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/detecting-twenty-thousand-classes-using-image","title":"Detecting Twenty-thousand Classes using Image-level Supervision","date":"2022-01-07","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/defrcn-decoupled-faster-r-cnn-for-few-shot","title":"DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection","date":"2021-08-20","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/fsce-few-shot-object-detection-via","title":"FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding","date":"2021-03-10","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/frustratingly-simple-few-shot-object","title":"Frustratingly Simple Few-Shot Object Detection","date":"2020-03-16","rows_on_this_dataset":1,"code_links":5,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":3,"samples_unverified":8,"pointer_only_for_licence":11,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/meta-rcnn-meta-learning-for-few-shot-object","title":"Meta-RCNN: Meta Learning for Few-Shot Object Detection","date":"2019-09-25","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":6,"samples_harvested":48,"samples_ran":29,"samples_unverified":19,"pointer_only_for_licence":11,"papers_with_no_sample_that_ran":1,"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."}