{"id":"W3108842862","doi":"10.1109/cvprw53098.2021.00508","title":"SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"King Abdullah University of Science and Technology; Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture; Aalborg Universitet; Waalse Gewest","keywords":"Computer science; Task (project management); Field (mathematics); Implementation; Benchmark (surveying); Artificial intelligence; Human–computer interaction; Video editing; Realm; Segmentation; Multimedia; Annotation; Machine learning; Software engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004261636,0.0002204192,0.0004778696,0.0001752415,0.0001097482,0.0005600505,0.0006091734,0.0001996122,0.0001339592],"category_scores_gemma":[0.0001130399,0.0002040331,0.0001548827,0.0002060865,0.0000645602,0.0002893014,0.001555689,0.0001835791,6.943595e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009463352,"about_ca_system_score_gemma":0.0001922629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003105565,"about_ca_topic_score_gemma":0.0002102229,"domain_scores_codex":[0.9982387,0.00006993576,0.0004619542,0.0007305153,0.0002801185,0.0002187155],"domain_scores_gemma":[0.9984881,0.000207052,0.0002840062,0.0007982187,0.0001328497,0.00008981501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005442937,0.0004898001,0.005545138,0.003668493,0.001932101,0.00004907823,0.004404861,0.009522925,0.001083733,0.7700374,0.1526089,0.05060324],"study_design_scores_gemma":[0.0006323291,0.00006715415,0.0006898227,0.0003039921,0.0003155009,0.000007936306,0.0007320206,0.9408984,0.0004092749,0.05220803,0.003071726,0.0006638456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007851417,0.0003932928,0.9965032,0.0004504854,0.0002550837,0.0002711133,0.0005755387,0.00002462182,0.0007415251],"genre_scores_gemma":[0.9320235,0.0003020444,0.05766305,0.0003691879,0.00009927872,0.0000371184,0.009292399,0.00001820202,0.0001952704],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9388402,"threshold_uncertainty_score":0.832023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1102522312492636,"score_gpt":0.3189543174245202,"score_spread":0.2087020861752566,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}