{"url":"/dataset/cholec80","name":"Cholec80","full_name":"Surgical Workflow Dataset","description_markdown":"Cholec80 is an endoscopic video dataset containing 80 videos of cholecystectomy surgeries performed by 13 surgeons. The videos are captured at 25 fps and downsampled to 1 fps for processing. The whole dataset is labeled with the phase and tool presence annotations. The phases have been defined by a senior surgeon in Strasbourg hospital, France. Since the tools are sometimes hardly visible in the images and thus difficult to be recognized visually, a tool is defined as present in an image if at least half of the tool tip is visible.\r\n\r\nSource: [EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos](/paper/endonet-a-deep-architecture-for-recognition)[https://arxiv.org/pdf/1602.03012.pdf]","description_withheld":null,"homepage":"http://camma.u-strasbg.fr/datasets","introduced_date":"2016-02-09","introduced_date_note":null,"introduced_by":{"paper":"/paper/endonet-a-deep-architecture-for-recognition","title":"EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos","first_author":"Andru P. Twinanda","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Medical","url":"/datasets/modality/medical"}],"tasks":[{"name":"Surgical phase recognition","url":"/task/surgical-phase-recognition","datasets_with_task":"/datasets/task/surgical-phase-recognition"},{"name":"Surgical tool detection","url":"/task/surgical-tool-detection","datasets_with_task":"/datasets/task/surgical-tool-detection"},{"name":"Online surgical phase recognition","url":"/task/online-surgical-phase-recognition","datasets_with_task":"/datasets/task/online-surgical-phase-recognition"},{"name":"Offline surgical phase recognition","url":"/task/offline-surgical-phase-recognition","datasets_with_task":"/datasets/task/offline-surgical-phase-recognition"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Cholec80"],"data_loaders":[],"num_papers_in_archive":134,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/surgical-phase-recognition-on-cholec80-1","task":"Surgical phase recognition","dataset_variant":"Cholec80","rows":6,"metrics":["F1","Acc"],"first_row_in_archive_order":{"model":"LoViT","paper":"/paper/lovit-long-video-transformer-for-surgical","metrics":{"F1":"90.24"},"code_links":[{"title":"MRUIL/LoViT","url":"https://github.com/MRUIL/LoViT"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/surgical-tool-detection-on-cholec80","task":"Surgical tool detection","dataset_variant":"Cholec80","rows":6,"metrics":["mAP"],"first_row_in_archive_order":{"model":"MoCo V2 Surg SSL - FCN head","paper":"/paper/dissecting-self-supervised-learning-methods","metrics":{"mAP":"93.5"},"code_links":[{"title":"camma-public/selfsupsurg","url":"https://github.com/camma-public/selfsupsurg"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/must-multi-scale-transformers-for-surgical","title":"MuST: Multi-Scale Transformers for Surgical Phase Recognition","date":"2024-07-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/self-supervised-learning-for-endoscopic-video","title":"Self-Supervised Learning for Endoscopic Video Analysis","date":"2023-08-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/sf-tmn-slowfast-temporal-modeling-network-for","title":"SF-TMN: SlowFast Temporal Modeling Network for Surgical Phase Recognition","date":"2023-06-15","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/lovit-long-video-transformer-for-surgical","title":"LoViT: Long Video Transformer for Surgical Phase Recognition","date":"2023-05-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/dissecting-self-supervised-learning-methods","title":"Dissecting Self-Supervised Learning Methods for Surgical Computer Vision","date":"2022-07-01","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/tecno-surgical-phase-recognition-with-multi","title":"TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks","date":"2020-03-24","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/multi-task-recurrent-convolutional-network","title":"Multi-Task Recurrent Convolutional Network with Correlation Loss for Surgical Video Analysis","date":"2019-07-13","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/weakly-supervised-convolutional-lstm-approach","title":"Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videos","date":"2018-12-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/weakly-supervised-learning-for-tool","title":"Weakly-Supervised Learning for Tool Localization in Laparoscopic Videos","date":"2018-06-14","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/endonet-a-deep-architecture-for-recognition","title":"EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos","date":"2016-02-09","rows_on_this_dataset":2,"code_links":9,"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."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":2,"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."}