{"url":"/dataset/repcount","name":"RepCount","full_name":"Repetitive Action Counting Dataset","description_markdown":"Counting repetitive actions are widely seen in human activities such as physical exercise. Existing methods focus on performing repetitive action counting in short videos, which is tough for dealing with longer videos in more realistic scenarios. In the data-driven era, the degradation of such generalization capability is mainly attributed to the lack of long video datasets. To complement this margin, we introduce a new large-scale repetitive action counting dataset called RepCount covering a wide variety of video lengths, along with more realistic situations where action interruption or action inconsistencies occur in the video. Besides, we also provide a fine-grained annotation of the action cycles instead of just counting annotation along with a numerical value. Such a dataset contains **1451**  videos with about **20000** \r\n annotations, which is more challenging.  Furthermore, the dataset consists of two subsets namely Part-A and Part-B. The videos in Part-A are fetched from YouTube, while the others in Part-B record simulated physical examinations by junior school students and teachers.","description_withheld":null,"homepage":"https://svip-lab.github.io/dataset/RepCount_dataset.html","introduced_date":"2022-04-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/transrac-encoding-multi-scale-temporal","title":"TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting","first_author":"Huazhang Hu","url":null},"license":null,"modalities":[],"tasks":[{"name":"Repetitive Action Counting","url":"/task/repetitive-action-counting","datasets_with_task":"/datasets/task/repetitive-action-counting"}],"languages":[],"variants":["RepCount"],"data_loaders":[],"num_papers_in_archive":15,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/repetitive-action-counting-on-repcount","task":"Repetitive Action Counting","dataset_variant":"RepCount","rows":6,"metrics":["OBO","MAE","OBZ","RMSE"],"first_row_in_archive_order":{"model":"ESCounts","paper":"/paper/every-shot-counts-using-exemplars-for","metrics":{"MAE":"0.213","OBO":"0.563","OBZ":"0.245","RMSE":"4.455"},"code_links":[{"title":"sinhasaptarshi/EveryShotCounts","url":"https://github.com/sinhasaptarshi/EveryShotCounts"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/repetitive-action-counting-with-hybrid","title":"Repetitive Action Counting with Hybrid Temporal Relation Modeling","date":"2024-12-10","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/a-short-note-on-evaluating-repnet-for","title":"A Short Note on Evaluating RepNet for Temporal Repetition Counting in Videos","date":"2024-11-13","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/every-shot-counts-using-exemplars-for","title":"Every Shot Counts: Using Exemplars for Repetition Counting in Videos","date":"2024-03-26","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/poserac-pose-saliency-transformer-for","title":"PoseRAC: Pose Saliency Transformer for Repetitive Action Counting","date":"2023-03-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/transrac-encoding-multi-scale-temporal","title":"TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting","date":"2022-04-03","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/counting-out-time-class-agnostic-video-1","title":"Counting Out Time: Class Agnostic Video Repetition Counting in the Wild","date":"2020-06-27","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":3,"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."}