{"id":"W2155830983","doi":"10.1109/cvpr.2008.4587704","title":"Stereoscopic inpainting: Joint color and depth completion from stereo images","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":169,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"National Science Foundation","keywords":"Inpainting; Artificial intelligence; Computer vision; Image warping; Computer science; Segmentation; Stereoscopy; Depth map; Image segmentation; View synthesis; Object (grammar); Image (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":[0.0004302045,0.0008028231,0.0007175732,0.0006361888,0.0002467066,0.0005367226,0.001193816,0.0005601218,0.001719915],"category_scores_gemma":[0.0009057252,0.0003893421,0.0006717175,0.0005318735,0.0003807168,0.0006166547,0.0008414729,0.0008491635,0.0005694914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002816724,"about_ca_system_score_gemma":0.0006239069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001452522,"about_ca_topic_score_gemma":0.002089916,"domain_scores_codex":[0.9996647,0.00003212734,0.00001209415,0.00006168606,0.000189792,0.00003969677],"domain_scores_gemma":[0.9996372,0.00007136947,0.00006116529,0.0001021894,0.00009798032,0.00003005264],"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":[0.0003369689,0.0001714089,0.0007583745,0.0002853159,0.0000705113,0.000255544,0.0002767815,0.06719919,0.2467357,0.007938906,0.005590509,0.6703808],"study_design_scores_gemma":[0.00008730096,0.0002177689,0.001311527,0.0000192369,0.00002864158,0.0007688517,0.00005790826,0.8326298,0.1494158,0.006327701,0.00909696,0.00003845279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01275087,0.0001285621,0.9856486,0.0000414356,0.00003752738,0.00004656811,0.0000816691,0.0005476777,0.0007171015],"genre_scores_gemma":[0.1171529,0.0001879143,0.8804469,0.00004828021,0.00006943425,0.00007339295,0.0002485621,0.00009811588,0.00167457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001719915,"threshold_uncertainty_score":0.005753696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04548570756323882,"score_gpt":0.2606591646344814,"score_spread":0.2151734570712425,"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."}}