{"url":"/dataset/opv2v","name":"OPV2V","full_name":null,"description_markdown":"**OPV2V** is a large-scale open simulated dataset for Vehicle-to-Vehicle perception. It contains over 70 interesting scenes, 11,464 frames, and 232,913 annotated 3D vehicle bounding boxes, collected from 8 towns in CARLA and a digital town of Culver City, Los Angeles.","description_withheld":null,"homepage":"https://mobility-lab.seas.ucla.edu/opv2v/","introduced_date":"2021-09-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/opv2v-an-open-benchmark-dataset-and-fusion","title":"OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication","first_author":"Runsheng Xu","url":null},"license":null,"modalities":[],"tasks":[{"name":"3D Object Detection","url":"/task/3d-object-detection","datasets_with_task":"/datasets/task/3d-object-detection"},{"name":"Monocular 3D Object Detection","url":"/task/monocular-3d-object-detection","datasets_with_task":"/datasets/task/monocular-3d-object-detection"}],"languages":[],"variants":["OPV2V"],"data_loaders":[{"repo":"https://github.com/ydk122024/how2comm","url":"https://github.com/ydk122024/how2comm","frameworks":["pytorch"]}],"num_papers_in_archive":78,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-object-detection-on-opv2v","task":"3D Object Detection","dataset_variant":"OPV2V","rows":5,"metrics":["AP@0.7@Default","AP@0.7@CulverCity"],"first_row_in_archive_order":{"model":"V2VNet (PointPillar backbone)","paper":"/paper/v2vnet-vehicle-to-vehicle-communication-for","metrics":{"AP@0.7@CulverCity":"0.734","AP@0.7@Default":"0.822"},"code_links":[{"title":"DerrickXuNu/OpenCOOD","url":"https://github.com/DerrickXuNu/OpenCOOD"},{"title":"coperception/coperception","url":"https://github.com/coperception/coperception"},{"title":"taco-group/stamp","url":"https://github.com/taco-group/stamp"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/monocular-3d-object-detection-on-opv2v","task":"Monocular 3D Object Detection","dataset_variant":"OPV2V","rows":1,"metrics":["AP50"],"first_row_in_archive_order":{"model":"Where2comm","paper":"/paper/where2comm-communication-efficient","metrics":{"AP50":"47.14"},"code_links":[{"title":"mediabrain-sjtu/where2comm","url":"https://github.com/mediabrain-sjtu/where2comm"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/where2comm-communication-efficient","title":"Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps","date":"2022-09-26","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":4,"samples_unverified":2,"pointer_only_for_licence":6,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/opv2v-an-open-benchmark-dataset-and-fusion","title":"OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication","date":"2021-09-16","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/v2vnet-vehicle-to-vehicle-communication-for","title":"V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction","date":"2020-08-17","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/f-cooper-feature-based-cooperative-perception","title":"F-Cooper: Feature based Cooperative Perception for Autonomous Vehicle Edge Computing System Using 3D Point Clouds","date":"2019-09-13","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/cooper-cooperative-perception-for-connected","title":"Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds","date":"2019-05-13","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":8,"samples_ran":6,"samples_unverified":2,"pointer_only_for_licence":8,"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."}