{"url":"/dataset/industreal","name":"IndustReal","full_name":"IndustReal Dataset of Egocentric Videos for Procedure Understanding","description_markdown":"IndustReal is an ego-centric, multi-modal dataset where 27 participants are challenged to perform assembly and maintenance procedures on a construction-toy car. The dataset is annotated for action recognition, assembly state detection, and procedure step recognition. IndustReal includes 38 execution errors in a total of 84 videos, with 14 exclusive to validation and test sets and therefore suitable for testing the robustness of algorithms against unseen errors in procedural tasks. IndustReal offers open-source 3D models for all parts to promote the use of synthetic data for scalable approaches on this dataset, as well as reproducibility. All assembly parts used in the dataset are 3D printed. This ensures reproducibility and future availability of the model and allows for growth via community effort.\r\n\r\nIndustReal can be used to test methods towards (video) procedure understanding, industrial automation, and to quantify performance of augmented reality applications.","description_withheld":null,"homepage":"https://timschoonbeek.github.io/industreal.html","introduced_date":"2023-10-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/industreal-a-dataset-for-procedure-step","title":"IndustReal: A Dataset for Procedure Step Recognition Handling Execution Errors in Egocentric Videos in an Industrial-Like Setting","first_author":"Tim J. Schoonbeek","url":null},"license":{"name":"Apache License 2.0","url":"http://www.apache.org/licenses/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"},{"name":"3D","url":"/datasets/modality/3d"},{"name":"Cad","url":"/datasets/modality/cad"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"},{"name":"Tracking","url":"/datasets/modality/tracking"},{"name":"Stereo","url":"/datasets/modality/stereo"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Action Recognition","url":"/task/action-recognition-in-videos","datasets_with_task":"/datasets/task/action-recognition-in-videos"},{"name":"Procedure Step Recognition","url":"/task/procedure-step-recognition","datasets_with_task":"/datasets/task/procedure-step-recognition"}],"languages":[],"variants":["IndustReal"],"data_loaders":[{"repo":"https://github.com/y-shinozaki/industreal","url":"https://github.com/y-shinozaki/industreal","frameworks":["pytorch"]}],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/object-detection-on-industreal","task":"Object Detection","dataset_variant":"IndustReal","rows":2,"metrics":["mAP"],"first_row_in_archive_order":{"model":"YoloV8","paper":"/paper/industreal-a-dataset-for-procedure-step","metrics":{"mAP":"64.1"},"code_links":[{"title":"timschoonbeek/industreal","url":"https://github.com/timschoonbeek/industreal"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/procedure-step-recognition-on-industreal","task":"Procedure Step Recognition","dataset_variant":"IndustReal","rows":2,"metrics":["Delay (seconds)","F1","POS"],"first_row_in_archive_order":{"model":"B3","paper":"/paper/industreal-a-dataset-for-procedure-step","metrics":{"Delay (seconds)":"22.4","F1":"0.883","POS":"0.797"},"code_links":[{"title":"timschoonbeek/industreal","url":"https://github.com/timschoonbeek/industreal"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/action-recognition-on-industreal","task":"Action Recognition","dataset_variant":"IndustReal","rows":1,"metrics":["Top-1","Top-5"],"first_row_in_archive_order":{"model":"MViT-V2","paper":"/paper/industreal-a-dataset-for-procedure-step","metrics":{"Top-1":"65.25","Top-5":"87.93"},"code_links":[{"title":"timschoonbeek/industreal","url":"https://github.com/timschoonbeek/industreal"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/industreal-a-dataset-for-procedure-step","title":"IndustReal: A Dataset for Procedure Step Recognition Handling Execution Errors in Egocentric Videos in an Industrial-Like Setting","date":"2023-10-26","rows_on_this_dataset":5,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":4,"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":1,"samples_harvested":5,"samples_ran":4,"samples_unverified":1,"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."}