{"id":"W4319300623","doi":"10.1109/wacv56688.2023.00426","title":"Multivariate Probabilistic Monocular 3D Object Detection","year":2023,"lang":"en","type":"article","venue":"2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Monocular; Artificial intelligence; Robustness (evolution); Probabilistic logic; Computer science; Covariance; Probability distribution; Multivariate statistics; Covariance matrix; Joint probability distribution; Computer vision; Posterior probability; Object detection; Pattern recognition (psychology); Mathematics; Machine learning; Algorithm; Bayesian probability; Statistics","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":[0.0008369396,0.00114697,0.001195504,0.0008372391,0.0003486596,0.0007495225,0.002007557,0.0009014193,0.001826678],"category_scores_gemma":[0.002612984,0.0007232877,0.000920946,0.001207606,0.0005022953,0.001399127,0.001679074,0.001025125,0.0009277905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000659148,"about_ca_system_score_gemma":0.0008649729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007714758,"about_ca_topic_score_gemma":0.01295943,"domain_scores_codex":[0.9989919,0.0001267715,0.00003050107,0.000357613,0.0003840795,0.0001091384],"domain_scores_gemma":[0.9990733,0.0002623026,0.0001176006,0.000242061,0.0002508443,0.00005400147],"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":[0.000263079,0.0001395272,0.005733829,0.0001467201,0.0001587533,0.0001451231,0.00008807844,0.3084724,0.02226574,0.005858554,0.008504009,0.6482241],"study_design_scores_gemma":[0.00000409003,0.00001649016,0.001582194,0.000004348386,0.000007217222,0.00008247968,0.000006521018,0.9924274,0.002469765,0.002457203,0.0009313895,0.00001088564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01777056,0.0003820658,0.9782603,0.0001618326,0.00004406926,0.0000338386,0.0004045255,0.001933186,0.001009544],"genre_scores_gemma":[0.5977948,0.0006608095,0.3943549,0.0003476544,0.0001062687,0.0001108848,0.002408171,0.000315431,0.003901021],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007714758,"threshold_uncertainty_score":0.01533967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02941803805642603,"score_gpt":0.3058455239599843,"score_spread":0.2764274859035583,"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."}}