{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003976253,0.00143658,0.0009215403,0.003400028,0.0005190574,0.001313606,0.001575324,0.001001401,0.005160767],"category_scores_gemma":[0.001844327,0.000302976,0.0009429115,0.002571789,0.000416885,0.001680271,0.001312719,0.0009321145,0.002173317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008985774,"about_ca_system_score_gemma":0.0006971333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009938746,"about_ca_topic_score_gemma":0.01771933,"domain_scores_codex":[0.9993054,0.000052663,0.0000396497,0.000352391,0.0001514638,0.00009843773],"domain_scores_gemma":[0.9993067,0.0001077018,0.00008865641,0.0002325293,0.0001953761,0.00006903627],"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":[0.001546088,0.0002526309,0.007128244,0.001769052,0.000295321,0.0007664612,0.0003364695,0.01829488,0.08528215,0.007040594,0.1179913,0.759297],"study_design_scores_gemma":[0.0001781181,0.0008364938,0.04721634,0.0005190442,0.0003701458,0.002779205,0.001232009,0.5599146,0.1389319,0.02212984,0.2257358,0.0001564442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2091207,0.00903255,0.5707663,0.001070386,0.001325077,0.002511382,0.1316122,0.0397274,0.03483409],"genre_scores_gemma":[0.3488547,0.002543435,0.4251286,0.00047018,0.0004448359,0.0006094312,0.2117465,0.001486362,0.008715965],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009938746,"threshold_uncertainty_score":0.0197618,"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."}}