{"id":"W4411408438","doi":"10.1109/tpami.2025.3578587","title":"Learning Lens Blur Fields","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Deconvolution; Artificial intelligence; Computer vision; Computer science; Depth of field; Point spread function; Lens (geology); Pixel; Image restoration; Blind deconvolution; Focus (optics); Gaussian blur; Global illumination; Optical transfer function; Multilayer perceptron; Artificial neural network; Optics; Image processing; Image (mathematics); Algorithm; 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":[0.0006451157,0.0009034546,0.0006644011,0.0008942105,0.0002277849,0.0008614624,0.0008688954,0.001010689,0.001415935],"category_scores_gemma":[0.002854333,0.0004533743,0.0007956048,0.0006079021,0.0003929871,0.001306784,0.0007294654,0.001176336,0.0005308135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009985864,"about_ca_system_score_gemma":0.0008370417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007026656,"about_ca_topic_score_gemma":0.007773004,"domain_scores_codex":[0.9996031,0.00006229755,0.00001822368,0.0001463989,0.0001094164,0.00006058528],"domain_scores_gemma":[0.9992346,0.0002301822,0.0001319507,0.0001182768,0.0002270941,0.00005795719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003609004,0.0002253872,0.00844022,0.0002922566,0.0001426734,0.000186697,0.0001081047,0.4966347,0.03199466,0.008732603,0.008616067,0.4442657],"study_design_scores_gemma":[0.000007570908,0.00003940152,0.001524253,0.00001587973,0.0000108125,0.00006263614,0.00001427365,0.9891807,0.005280256,0.002745376,0.001106986,0.00001177608],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08969092,0.001176067,0.9041649,0.0003069304,0.00008214913,0.00006014356,0.0008130582,0.001715572,0.001990384],"genre_scores_gemma":[0.8066431,0.0008390535,0.1843042,0.0002566608,0.0001050992,0.00005955196,0.002282311,0.0001596069,0.005350377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007026656,"threshold_uncertainty_score":0.01397151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01243228442271956,"score_gpt":0.2657429001060793,"score_spread":0.2533106156833598,"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."}}