{"url":"/dataset/mvsec-seg","name":"MVSEC-SEG","full_name":null,"description_markdown":"Based on the [MVSEC](https://daniilidis-group.github.io/mvsec/) dataset, we select some image-event pairs to evaluate the segmentation performance, namely MVSEC-SEG, which only serves as a test set. The MVSEC-SEG consists of 500 image-event pairs each in ”indoor flying1” and ”outdoor day2” sequences, containing 54,600 masks.","description_withheld":null,"homepage":"","introduced_date":"2023-12-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/segment-any-events-via-weighted-adaptation-of","title":"Segment Any Events via Weighted Adaptation of Pivotal Tokens","first_author":"Zhiwen Chen","url":null},"license":null,"modalities":[],"tasks":[{"name":"Event-based Object Segmentation","url":"/task/event-based-object-segmentation","datasets_with_task":"/datasets/task/event-based-object-segmentation"}],"languages":[],"variants":["MVSEC-SEG"],"data_loaders":[],"num_papers_in_archive":8,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/event-based-object-segmentation-on-mvsec-seg","task":"Event-based Object Segmentation","dataset_variant":"MVSEC-SEG","rows":8,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"EventSAM","paper":"/paper/segment-any-events-via-weighted-adaptation-of","metrics":{"mIoU":"0.40"},"code_links":[{"title":"happychenpipi/eventsam","url":"https://github.com/happychenpipi/eventsam"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/segment-any-events-via-weighted-adaptation-of","title":"Segment Any Events via Weighted Adaptation of Pivotal Tokens","date":"2023-12-24","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":6,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/segment-anything","title":"Segment Anything","date":"2023-04-05","rows_on_this_dataset":1,"code_links":32,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":23,"samples_ran":8,"samples_unverified":15,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/ess-learning-event-based-semantic","title":"ESS: Learning Event-based Semantic Segmentation from Still Images","date":"2022-03-18","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/evdistill-asynchronous-events-to-end-task-1","title":"EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation","date":"2021-11-24","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":17,"samples_ran":10,"samples_unverified":7,"pointer_only_for_licence":17,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dual-transfer-learning-for-event-based-end","title":"Dual Transfer Learning for Event-based End-task Prediction via Pluggable Event to Image Translation","date":"2021-09-04","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":3,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/event-based-video-reconstruction-using","title":"Event-Based Video Reconstruction Using Transformer","date":"2021-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/exploiting-event-cameras-by-using-a-network","title":"Learning to Exploit Multiple Vision Modalities by Using Grafted Networks","date":"2020-03-24","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/high-speed-and-high-dynamic-range-video-with","title":"High Speed and High Dynamic Range Video with an Event Camera","date":"2019-06-15","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":1,"samples_unverified":1,"pointer_only_for_licence":2,"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":62,"samples_ran":28,"samples_unverified":34,"pointer_only_for_licence":19,"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."}