{"url":"/dataset/endoslam","name":"EndoSLAM","full_name":"Endoscopic SLAM dataset","description_markdown":"The endoscopic SLAM dataset (**EndoSLAM**) is a dataset for depth estimation approach for endoscopic videos. It consists of both ex-vivo and synthetically generated data. The ex-vivo part of the dataset includes standard as well as capsule endoscopy recordings. The dataset is divided into 35 sub-datasets. Specifically, 18, 5 and 12 sub-datasets exist for colon, small intestine and stomach respectively.\n\nSource: [https://github.com/CapsuleEndoscope/EndoSLAM](https://github.com/CapsuleEndoscope/EndoSLAM)\nImage Source: [https://github.com/CapsuleEndoscope/EndoSLAM](https://github.com/CapsuleEndoscope/EndoSLAM)","description_withheld":null,"homepage":"https://github.com/CapsuleEndoscope/EndoSLAM","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/quantitative-evaluation-of-endoscopic-slam","title":"EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner","first_author":"Kutsev Bengisu Ozyoruk","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Depth Estimation","url":"/task/depth-estimation","datasets_with_task":"/datasets/task/depth-estimation"},{"name":"Visual Odometry","url":"/task/visual-odometry","datasets_with_task":"/datasets/task/visual-odometry"},{"name":"Monocular Visual Odometry","url":"/task/monocular-visual-odometry","datasets_with_task":"/datasets/task/monocular-visual-odometry"}],"languages":[],"variants":["EndoSLAM"],"data_loaders":[{"repo":"https://github.com/CapsuleEndoscope/EndoSLAM","url":"https://github.com/CapsuleEndoscope/EndoSLAM","frameworks":[]}],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"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."}