{"id":"W3035549667","doi":"10.1109/cvpr42600.2020.00988","title":"Video Panoptic Segmentation","year":2020,"lang":"en","type":"article","venue":"","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":163,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Segmentation; Panopticon; Artificial intelligence; Computer vision; Video tracking; Task (project management); Object (grammar)","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":[0.00003439023,0.00003331906,0.0000318177,0.0000164144,0.00003945759,0.00006323653,0.0001356323,0.000011749,0.00009673568],"category_scores_gemma":[0.00001058799,0.00002860662,0.00002169821,0.0002039326,0.000004499993,0.000299039,0.00003701255,0.00002632902,0.0005937269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007337922,"about_ca_system_score_gemma":0.000006487266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003136331,"about_ca_topic_score_gemma":7.594821e-7,"domain_scores_codex":[0.9996106,0.00001671335,0.00007449942,0.0001324508,0.0001036442,0.00006207466],"domain_scores_gemma":[0.9998345,0.000006068946,0.00001582024,0.00007061625,0.00001783148,0.00005517057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001191829,0.0001056473,0.002162891,0.00003581648,0.00002378849,0.00001321339,0.00394689,0.0003092162,0.3488012,0.2507183,0.01154636,0.3823248],"study_design_scores_gemma":[0.0008473393,0.0006172475,0.009452653,0.000005774652,0.000007191647,0.00001332229,0.0003588299,0.8125468,0.1592815,0.003168546,0.01333922,0.0003615023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02235498,0.0000045591,0.9668065,0.004804121,0.0001363554,0.00004778707,7.243361e-8,0.000267844,0.005577833],"genre_scores_gemma":[0.979587,0.000001796382,0.01641503,0.003643826,0.00002908518,0.000003600889,5.730111e-7,0.000001656975,0.0003174584],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.957232,"threshold_uncertainty_score":0.7631356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03123861564110416,"score_gpt":0.2665508728988404,"score_spread":0.2353122572577362,"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."}}