{"id":"W4293868165","doi":"10.1109/crv55824.2022.00025","title":"Occlusion-Aware Self-Supervised Stereo Matching with Confidence Guided Raw Disparity Fusion","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial intelligence; Computer science; Pipeline (software); Matching (statistics); Computer vision; Pattern recognition (psychology); Feature extraction; Feature (linguistics); Artificial neural network; Mathematics","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":[0.000644078,0.000800991,0.0008591228,0.001075832,0.0003257751,0.0006283273,0.002163285,0.0007145671,0.002602179],"category_scores_gemma":[0.002383405,0.0005193672,0.0007191299,0.0008442119,0.0003716188,0.001315127,0.00201192,0.0009742183,0.0006849963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006972768,"about_ca_system_score_gemma":0.001317872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003912526,"about_ca_topic_score_gemma":0.005938223,"domain_scores_codex":[0.9992859,0.00005305557,0.00003969876,0.0001763209,0.0003637181,0.00008143589],"domain_scores_gemma":[0.9990722,0.0001157305,0.0001552854,0.0002377415,0.0003755579,0.00004343532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003808677,0.0003073004,0.003955839,0.0001293358,0.000129571,0.0001232511,0.0002008251,0.1766104,0.06485745,0.00484019,0.004895057,0.7435699],"study_design_scores_gemma":[0.00002011554,0.00005597078,0.001148748,0.000007928986,0.00001833043,0.00009000322,0.00001727927,0.9772639,0.0179168,0.00251762,0.0009281602,0.00001506443],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03719585,0.0001108905,0.9583651,0.00006981548,0.00003766378,0.0000793254,0.0001663751,0.002370769,0.001604232],"genre_scores_gemma":[0.5619569,0.00009434207,0.4346521,0.0001802662,0.00004183267,0.0000947611,0.0007822438,0.0002476121,0.001949931],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003912526,"threshold_uncertainty_score":0.008705199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01465928784878171,"score_gpt":0.2645742449071681,"score_spread":0.2499149570583864,"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."}}