{"url":"/dataset/soccernet-v2","name":"SoccerNet-v2","full_name":null,"description_markdown":"A novel large-scale corpus of manual annotations for the SoccerNet video dataset, along with open challenges to encourage more research in soccer understanding and broadcast production.\r\n\r\nSource: [SoccerNet-v2 : A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos](/paper/soccernet-v2-a-dataset-and-benchmarks-for)","description_withheld":null,"homepage":"https://soccer-net.org/","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/soccernet-v2-a-dataset-and-benchmarks-for","title":"SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos","first_author":"Adrien Deliège","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Person Re-Identification","url":"/task/person-re-identification","datasets_with_task":"/datasets/task/person-re-identification"},{"name":"Action Classification","url":"/task/action-classification","datasets_with_task":"/datasets/task/action-classification"},{"name":"Video Understanding","url":"/task/video-understanding","datasets_with_task":"/datasets/task/video-understanding"},{"name":"Boundary Detection","url":"/task/boundary-detection","datasets_with_task":"/datasets/task/boundary-detection"},{"name":"Video Object Tracking","url":"/task/video-object-tracking","datasets_with_task":"/datasets/task/video-object-tracking"},{"name":"Camera shot boundary detection","url":"/task/camera-shot-boundary-detection","datasets_with_task":"/datasets/task/camera-shot-boundary-detection"},{"name":"Action Spotting","url":"/task/action-spotting","datasets_with_task":"/datasets/task/action-spotting"},{"name":"Camera shot segmentation","url":"/task/camera-shot-segmentation","datasets_with_task":"/datasets/task/camera-shot-segmentation"},{"name":"Replay Grounding","url":"/task/replay-grounding","datasets_with_task":"/datasets/task/replay-grounding"}],"languages":[],"variants":["SoccerNet","SoccerNet-v2"],"data_loaders":[],"num_papers_in_archive":58,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/action-spotting-on-soccernet-v2","task":"Action Spotting","dataset_variant":"SoccerNet-v2","rows":10,"metrics":["Tight Average-mAP","Average-mAP"],"first_row_in_archive_order":{"model":"COMEDIAN (ViSwin T ens.)","paper":"/paper/comedian-self-supervised-learning-and","metrics":{"Average-mAP":"77.6","Tight Average-mAP":"73.1"},"code_links":[{"title":"juliendenize/eztorch","url":"https://github.com/juliendenize/eztorch"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/camera-shot-boundary-detection-on-soccernet","task":"Camera shot boundary detection","dataset_variant":"SoccerNet-v2","rows":4,"metrics":["mAP"],"first_row_in_archive_order":{"model":"Histogram (Scikit-Video)","paper":"/paper/soccernet-v2-a-dataset-and-benchmarks-for","metrics":{"mAP":"78.5"},"code_links":[{"title":"SilvioGiancola/SoccerNetv2-DevKit","url":"https://github.com/SilvioGiancola/SoccerNetv2-DevKit"},{"title":"soccernet/sn-spotting","url":"https://github.com/soccernet/sn-spotting"},{"title":"aimagelab/rmsnet_soccer","url":"https://github.com/aimagelab/rmsnet_soccer"},{"title":"soccernet/sn-grounding","url":"https://github.com/soccernet/sn-grounding"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/camera-shot-segmentation-on-soccernet-v2","task":"Camera shot segmentation","dataset_variant":"SoccerNet-v2","rows":2,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"CALF (Cioppa et al.)","paper":"/paper/soccernet-v2-a-dataset-and-benchmarks-for","metrics":{"mIoU":"47.3"},"code_links":[{"title":"SilvioGiancola/SoccerNetv2-DevKit","url":"https://github.com/SilvioGiancola/SoccerNetv2-DevKit"},{"title":"soccernet/sn-spotting","url":"https://github.com/soccernet/sn-spotting"},{"title":"aimagelab/rmsnet_soccer","url":"https://github.com/aimagelab/rmsnet_soccer"},{"title":"soccernet/sn-grounding","url":"https://github.com/soccernet/sn-grounding"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/replay-grounding-on-soccernet-v2","task":"Replay Grounding","dataset_variant":"SoccerNet-v2","rows":2,"metrics":["Average-AP"],"first_row_in_archive_order":{"model":"CALF (Cioppa et al.)","paper":"/paper/soccernet-v2-a-dataset-and-benchmarks-for","metrics":{"Average-AP":"41.8"},"code_links":[{"title":"SilvioGiancola/SoccerNetv2-DevKit","url":"https://github.com/SilvioGiancola/SoccerNetv2-DevKit"},{"title":"soccernet/sn-spotting","url":"https://github.com/soccernet/sn-spotting"},{"title":"aimagelab/rmsnet_soccer","url":"https://github.com/aimagelab/rmsnet_soccer"},{"title":"soccernet/sn-grounding","url":"https://github.com/soccernet/sn-grounding"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/person-re-identification-on-soccernet-v2","task":"Person Re-Identification","dataset_variant":"SoccerNet-v2","rows":1,"metrics":["Rank-1","mAP"],"first_row_in_archive_order":{"model":"ViT-B/16","paper":"/paper/sports-re-id-improving-re-identification-of","metrics":{"Rank-1":"81.5","mAP":"86.0"},"code_links":[{"title":"shallowlearn/sportsreid","url":"https://github.com/shallowlearn/sportsreid"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/video-object-tracking-on-soccernet-v2","task":"Video Object Tracking","dataset_variant":"SoccerNet-v2","rows":1,"metrics":["HOTA"],"first_row_in_archive_order":{"model":"CO-MOT","paper":"/paper/bridging-the-gap-between-end-to-end-and-non","metrics":{"HOTA":"69.54"},"code_links":[{"title":"bingfengyan/visam","url":"https://github.com/bingfengyan/visam"},{"title":"BingfengYan/CO-MOT","url":"https://github.com/BingfengYan/CO-MOT"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/comedian-self-supervised-learning-and","title":"COMEDIAN: Self-Supervised Learning and Knowledge Distillation for Action Spotting using Transformers","date":"2023-09-03","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/bridging-the-gap-between-end-to-end-and-non","title":"Bridging the Gap Between End-to-end and Non-End-to-end Multi-Object Tracking","date":"2023-05-22","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/spotting-temporally-precise-fine-grained","title":"Spotting Temporally Precise, Fine-Grained Events in Video","date":"2022-07-20","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":1,"samples_unverified":4,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/action-spotting-using-dense-detection-anchors","title":"Action Spotting using Dense Detection Anchors Revisited: Submission to the SoccerNet Challenge 2022","date":"2022-06-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/sports-re-id-improving-re-identification-of","title":"Sports Re-ID: Improving Re-Identification Of Players In Broadcast Videos Of Team Sports","date":"2022-06-06","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/temporally-aware-feature-pooling-for-action","title":"Temporally-Aware Feature Pooling for Action Spotting in Soccer Broadcasts","date":"2021-04-14","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/soccernet-v2-a-dataset-and-benchmarks-for","title":"SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos","date":"2020-11-26","rows_on_this_dataset":10,"code_links":4,"syntology":null},{"paper":"/paper/a-context-aware-loss-function-for-action","title":"A Context-Aware Loss Function for Action Spotting in Soccer Videos","date":"2019-12-03","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":5,"samples_ran":1,"samples_unverified":4,"pointer_only_for_licence":1,"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."}