{"id":"W4389665500","doi":"10.1109/iros55552.2023.10341610","title":"Pseudo-Stereo++: Cycled Generative Pseudo-Stereo for Monocular 3D Object Detection in Autonomous Driving","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Artificial intelligence; Monocular; Computer vision; Computer science; Object detection; Benchmark (surveying); Stereopsis; Object (grammar); Detector; Stereo cameras; Feature (linguistics); Pattern recognition (psychology); Geology","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":[0.0005275481,0.0008582507,0.0004222701,0.0006977747,0.0002511205,0.0005864708,0.001953059,0.0007594683,0.005943869],"category_scores_gemma":[0.0008886462,0.0004358131,0.0008856162,0.0004018722,0.0004782396,0.0006532798,0.001275337,0.0007190223,0.00160184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004561813,"about_ca_system_score_gemma":0.0006625323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003284693,"about_ca_topic_score_gemma":0.004274935,"domain_scores_codex":[0.9995147,0.00006604157,0.00001505709,0.00009808731,0.0002580823,0.00004808762],"domain_scores_gemma":[0.9996948,0.00006782967,0.00002099274,0.00009795775,0.00009355416,0.00002483351],"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":[0.0002734093,0.0001371348,0.001252975,0.0002089264,0.00009027129,0.0002452228,0.0002014708,0.1065111,0.09339749,0.01466475,0.01158951,0.7714278],"study_design_scores_gemma":[0.00003525847,0.0001193605,0.0004834076,0.0000126116,0.00001831673,0.0002773912,0.00002407794,0.9350477,0.04424667,0.006281957,0.01342624,0.00002705411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007919637,0.0001714634,0.9816296,0.00004689507,0.00004775,0.00007828292,0.0001674504,0.00748103,0.002457895],"genre_scores_gemma":[0.1918491,0.0002176852,0.8016354,0.0001832359,0.00004135711,0.0001633827,0.001069714,0.0009845934,0.003855551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005943869,"threshold_uncertainty_score":0.01988423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02328865735101092,"score_gpt":0.2815439479510987,"score_spread":0.2582552906000877,"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."}}