{"url":"/dataset/gen1-detection","name":"GEN1 Detection","full_name":"Prophesee GEN1 Automotive Detection Dataset","description_markdown":"Prophesee’s GEN1 Automotive Detection Dataset is the largest Event-Based Dataset to date.\r\n\r\nThe dataset was recorded using a PROPHESEE GEN1 sensor with a resolution of 304×240 pixels, mounted on a car dashboard. The labels were obtained using the gray level estimation feature of the ATIS camera by labelling manually.\r\n\r\nIt contains 39 hours of open road and various driving scenarios ranging from urban, highway, suburbs and countryside scenes.\r\n\r\nManual bounding box annotations are available for two classes are present: pedestrians and cars. (Truck and buses are not labelled).","description_withheld":null,"homepage":"https://www.prophesee.ai/2020/01/24/prophesee-gen1-automotive-detection-dataset/","introduced_date":"2020-01-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-large-scale-event-based-detection-dataset","title":"A Large Scale Event-based Detection Dataset for Automotive","first_author":"Pierre de Tournemire","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"2D Object Detection","url":"/task/2d-object-detection","datasets_with_task":"/datasets/task/2d-object-detection"},{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Video Object Detection","url":"/task/video-object-detection","datasets_with_task":"/datasets/task/video-object-detection"}],"languages":[],"variants":["GEN1 Detection"],"data_loaders":[],"num_papers_in_archive":13,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/object-detection-on-gen1-detection","task":"Object Detection","dataset_variant":"GEN1 Detection","rows":11,"metrics":["mAP","Params"],"first_row_in_archive_order":{"model":"ERGO-12","paper":"/paper/from-chaos-comes-order-ordering-event","metrics":{"Params":"59.6","mAP":"50.4"},"code_links":[{"title":"uzh-rpg/event_representation_study","url":"https://github.com/uzh-rpg/event_representation_study"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/state-space-models-for-event-cameras","title":"State Space Models for Event Cameras","date":"2024-02-23","rows_on_this_dataset":2,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":19,"samples_ran":5,"samples_unverified":14,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/get-group-event-transformer-for-event-based-1","title":"GET: Group Event Transformer for Event-Based Vision","date":"2023-10-04","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":8,"samples_unverified":3,"pointer_only_for_licence":11,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/hierarchical-neural-memory-network-for-low-1","title":"Hierarchical Neural Memory Network for Low Latency Event Processing","date":"2023-05-29","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":0,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/from-chaos-comes-order-ordering-event","title":"From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection","date":"2023-04-26","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/recurrent-vision-transformers-for-object","title":"Recurrent Vision Transformers for Object Detection with Event Cameras","date":"2022-12-11","rows_on_this_dataset":3,"code_links":1,"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."}},{"paper":"/paper/object-detection-with-spiking-neural-networks","title":"Object Detection with Spiking Neural Networks on Automotive Event Data","date":"2022-05-09","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"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":5,"samples_harvested":38,"samples_ran":14,"samples_unverified":24,"pointer_only_for_licence":12,"papers_with_no_sample_that_ran":2,"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."}