{"id":"W4402904139","doi":"10.1109/cvprw63382.2024.00005","title":"The Third Monocular Depth Estimation Challenge","year":2024,"lang":"en","type":"article","venue":"","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Engineering and Physical Sciences Research Council","keywords":"Monocular; Estimation; Computer science; Artificial intelligence; Computer vision; Geology; Engineering","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":[0.00006036506,0.00004245433,0.00002387875,0.0000139645,0.00007183572,0.0001223866,0.00007196336,0.00002146582,0.000008339253],"category_scores_gemma":[0.000003166261,0.00002748556,0.00001771042,0.00007507724,0.00001085821,0.00006928548,0.000009372227,0.00006490219,0.00009348991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001383268,"about_ca_system_score_gemma":0.000004465713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002551114,"about_ca_topic_score_gemma":0.000003797429,"domain_scores_codex":[0.9997732,0.000001722611,0.00005838215,0.00005434562,0.00004068314,0.00007168622],"domain_scores_gemma":[0.9998488,0.00001978139,0.000002337746,0.0001089998,0.000008152224,0.00001192152],"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":[2.022663e-7,0.000003691004,8.089617e-7,0.00006683846,0.00001204408,0.000001294589,0.0001027562,0.001536949,0.0006453028,0.09813793,0.02098064,0.8785115],"study_design_scores_gemma":[0.000006685927,0.000002310295,0.000008123339,0.0000126291,0.000003555578,0.000001720044,0.000008332757,0.8660654,0.003677835,0.01961419,0.1105585,0.00004069636],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001796787,0.003861592,0.9002863,0.001217645,0.00005880878,0.00007285961,4.341551e-7,0.002150386,0.09217226],"genre_scores_gemma":[0.9472353,0.0006110207,0.05112489,0.00002035626,0.00004336801,0.0001039918,0.000002658232,0.00001859195,0.0008397886],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9470556,"threshold_uncertainty_score":0.1201655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01423954823804031,"score_gpt":0.2648189465079417,"score_spread":0.2505793982699014,"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."}}