{"url":"/dataset/hazards-robots","name":"Hazards&Robots","full_name":"Hazards&Robots: A Dataset for Visual Anomaly Detection in Robotics","description_markdown":"We consider the problem of detecting, in the visual sensing data stream of an autonomous mobile robot, semantic patterns that are unusual (i.e., anomalous) with respect to the robot’s previous experience in similar environments. These anomalies might indicate unforeseen hazards and, in scenarios where failure is costly, can be used to trigger an avoidance behavior. We contribute three novel image-based datasets acquired in robot exploration scenarios, comprising a total of more than 200k labeled frames, spanning various types of anomalies.","description_withheld":null,"homepage":"https://github.com/idsia-robotics/hazard-detection","introduced_date":"2022-09-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/an-outlier-exposure-approach-to-improve","title":"An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots","first_author":"Dario Mantegazza","url":null},"license":{"name":"Creative Commons Attribution 4.0 International","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Anomaly Detection","url":"/task/anomaly-detection","datasets_with_task":"/datasets/task/anomaly-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Hazards&Robots"],"data_loaders":[],"num_papers_in_archive":3,"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":"2026-09-25T09:33:49+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."}