{"id":"W2151860947","doi":"10.1109/3dim.2005.40","title":"Fast Multiple-Baseline Stereo with Occlusion","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; University of Tsukuba","keywords":"Visibility; Baseline (sea); Heuristics; Computer science; Ground truth; Artificial intelligence; Computer vision; Dynamic programming; Stereopsis; Heuristic; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00009441167,0.00008372769,0.0000708574,0.0000514628,0.00008789237,0.00006225581,0.0003209258,0.00001262718,0.00006957803],"category_scores_gemma":[0.00001553926,0.00005494002,0.00001821925,0.0001721836,0.00001773242,0.0006341527,0.0001829065,0.00006561414,0.0001975129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001845748,"about_ca_system_score_gemma":0.00001731167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000540475,"about_ca_topic_score_gemma":0.00002707341,"domain_scores_codex":[0.9993052,0.00001678358,0.0001064427,0.0002346704,0.0001681245,0.00016873],"domain_scores_gemma":[0.9994644,0.00004829514,0.00003011509,0.0003298045,0.00004955912,0.0000778323],"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":[0.000009214077,0.00005084326,0.001157011,0.000001907294,0.000002030654,0.00001060926,0.0001750714,0.001145974,0.001680967,0.002028742,0.001218802,0.9925188],"study_design_scores_gemma":[0.0006428501,0.00004941612,0.0006745903,0.0000172026,8.405105e-7,0.00003270444,0.00003236562,0.9359134,0.007261911,0.00005717126,0.05517826,0.0001392629],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002483896,0.00003091088,0.9883456,0.003269622,0.00004805011,0.00006124667,3.412859e-7,0.0002294658,0.005530819],"genre_scores_gemma":[0.4121465,0.00000414643,0.5835211,0.002296602,0.00004801702,0.000001020161,7.931402e-7,0.000004450449,0.001977354],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9923795,"threshold_uncertainty_score":0.2538694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009686123230179778,"score_gpt":0.25177558222735,"score_spread":0.2420894589971702,"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."}}