{"id":"W3136263466","doi":"10.1109/cvprw53098.2021.00317","title":"Video Class Agnostic Segmentation Benchmark for Autonomous Driving","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Segmentation; Computer science; Benchmark (surveying); Artificial intelligence; Class (philosophy); Computer vision; Set (abstract data type); Task (project management); Baseline (sea); Motion (physics); Scale-space segmentation; Robotics; Image segmentation; Machine learning; Robot","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":[0.001905867,0.002873634,0.001514184,0.002944432,0.001251769,0.002015019,0.003689255,0.003668493,0.0031347],"category_scores_gemma":[0.004692044,0.0006504702,0.001587012,0.002545769,0.001160469,0.00196979,0.001846248,0.002205539,0.002298701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002352022,"about_ca_system_score_gemma":0.001723844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03106513,"about_ca_topic_score_gemma":0.04048105,"domain_scores_codex":[0.9982535,0.0002388067,0.0001055184,0.0007769294,0.0004141632,0.0002111022],"domain_scores_gemma":[0.998185,0.0005339177,0.0001200387,0.0004332065,0.0005444143,0.0001834102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002863765,0.002611754,0.01107651,0.002446157,0.000893216,0.0006492026,0.0004403829,0.4139109,0.0282414,0.006641601,0.1683346,0.3618905],"study_design_scores_gemma":[0.0002288379,0.0005733836,0.007417638,0.0001218065,0.00009819106,0.0004743617,0.0002847187,0.9335957,0.02475854,0.008317603,0.02403606,0.00009316573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6818243,0.008684292,0.1466801,0.002603826,0.002071519,0.001612662,0.07705902,0.04736967,0.03209474],"genre_scores_gemma":[0.5727056,0.001335904,0.1805962,0.0009079449,0.00031973,0.0006254835,0.2297991,0.00309972,0.01061032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03106513,"threshold_uncertainty_score":0.06176865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02141733507135049,"score_gpt":0.2901025194071777,"score_spread":0.2686851843358272,"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."}}