{"id":"W2007653165","doi":"10.1109/cvpr.2014.90","title":"Frequency-Based 3D Reconstruction of Transparent and Specular Objects","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Specular reflection; Computer vision; Computer science; Artificial intelligence; Pixel; Specular highlight; Frequency domain; SIGNAL (programming language); Structured light; 3D reconstruction; Set (abstract data type); Fourier transform; Computer graphics (images); Optics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003907197,0.0008368161,0.0005895857,0.001445235,0.0002490031,0.001110989,0.0005776153,0.0009339419,0.001467701],"category_scores_gemma":[0.001013758,0.0006733314,0.0008674581,0.001036748,0.0004938057,0.0009684635,0.000888827,0.001039913,0.0007637743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00031953,"about_ca_system_score_gemma":0.0005149907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001079938,"about_ca_topic_score_gemma":0.001672299,"domain_scores_codex":[0.9996198,0.00004563787,0.00001418841,0.00005184767,0.0002326656,0.00003586649],"domain_scores_gemma":[0.999513,0.0001038055,0.00007009331,0.0001531681,0.0001297747,0.00003017733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004073051,0.0001385477,0.002754705,0.0003223484,0.000123905,0.0007265788,0.0005016903,0.1620706,0.5169771,0.0141626,0.002914648,0.2989],"study_design_scores_gemma":[0.00002734789,0.0000793258,0.002922626,0.00002890149,0.00003366245,0.001161898,0.0001418639,0.8639032,0.1223239,0.005462715,0.003823681,0.00009101412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0646548,0.000145558,0.9325127,0.00006887946,0.00002444334,0.00002400703,0.0001380482,0.0006348128,0.001796702],"genre_scores_gemma":[0.3238393,0.0005307358,0.6722948,0.00006446013,0.00002949287,0.00004080404,0.0006351039,0.0002914125,0.00227391],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001467701,"threshold_uncertainty_score":0.004909933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01320367447443574,"score_gpt":0.2419428655704686,"score_spread":0.2287391910960328,"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."}}