{"id":"W2327449852","doi":"10.1109/tpami.2016.2545662","title":"3D Shape and Indirect Appearance by Structured Light Transport","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Society of General Physiologists","keywords":"Epipolar geometry; Computer vision; Projector; Structured light; Computer science; Artificial intelligence; Ray; Light field; Photometric stereo; Computer graphics (images); Optics; Image (mathematics); Physics","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":[0.0001348692,0.0002388451,0.0003229349,0.000325228,0.0001964319,0.00007237586,0.0003409611,0.0000540716,0.0001455285],"category_scores_gemma":[0.000002631737,0.000161564,0.0001325657,0.0006768774,0.00008216884,0.0004316842,0.000004623821,0.0001687915,0.00001388979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001872444,"about_ca_system_score_gemma":0.00001015201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008827879,"about_ca_topic_score_gemma":0.0002194844,"domain_scores_codex":[0.9984835,0.00004968776,0.0003189148,0.0006495326,0.0002407162,0.0002576079],"domain_scores_gemma":[0.9992412,0.00006143381,0.00008776154,0.000399152,0.00004320549,0.0001672197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00000846388,0.00003893684,0.001079101,0.000007419468,0.0001374516,0.000005412121,0.0001894343,0.0001463111,0.006186055,0.00001392667,0.000007905979,0.9921796],"study_design_scores_gemma":[0.000540819,0.0002339549,0.007484498,0.0001737834,0.0004476676,0.00004744884,0.00004080307,0.2354497,0.7513311,0.0006699477,0.002602811,0.0009775106],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005632314,0.0004985213,0.9923069,0.001168608,0.0001173874,0.00008900512,0.00004457984,0.00009756591,0.00004512124],"genre_scores_gemma":[0.9951795,0.001164574,0.00277206,0.0005655264,0.00001004962,0.000009894285,0.000001280667,0.00001137411,0.0002856978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9912021,"threshold_uncertainty_score":0.6588389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01072174793984231,"score_gpt":0.2543182374383721,"score_spread":0.2435964894985297,"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."}}