{"id":"W3118836296","doi":"10.1109/wacv48630.2021.00103","title":"AutoRetouch: Automatic Professional Face Retouching","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Quest University Canada","funders":"","keywords":"Face (sociological concept); Computer science; Smoothing; Artificial intelligence; Computer vision; Photography; Facial recognition system; Texture (cosmology); Computer graphics (images); Pattern recognition (psychology); Image (mathematics); Visual arts; Art","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002020951,0.0001274988,0.0001460169,0.00005404729,0.0001767459,0.0002013088,0.0007060716,0.0000547206,0.00008886355],"category_scores_gemma":[0.000283021,0.0001083793,0.00004303483,0.0004480676,0.00003492565,0.001083406,0.0006046057,0.0001909488,0.00005583339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005532304,"about_ca_system_score_gemma":0.0002829685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001523981,"about_ca_topic_score_gemma":9.671994e-7,"domain_scores_codex":[0.9986984,0.00007655197,0.0002321784,0.0004077424,0.0003264475,0.0002587278],"domain_scores_gemma":[0.9989826,0.00009968271,0.00008458659,0.0006137162,0.0001450815,0.00007431578],"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":[0.000002235775,0.0002934957,0.0006201171,0.0002106746,0.00003073598,0.0003674119,0.002978251,0.00002336812,0.1265786,0.3534411,0.03547078,0.4799832],"study_design_scores_gemma":[0.0002029531,0.00002787931,0.0008332038,0.0002266213,0.000004361465,0.0001884258,0.000151168,0.664095,0.1788173,0.1477267,0.007278218,0.0004482091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001604371,0.0001578456,0.9841858,0.00391251,0.0002928749,0.00007412759,3.498928e-7,0.002342776,0.007429384],"genre_scores_gemma":[0.0888955,0.000003976179,0.9045851,0.001283272,0.00002962106,0.00001713039,0.000001755166,0.00001044576,0.005173205],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6640717,"threshold_uncertainty_score":0.4419581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01487521148301244,"score_gpt":0.2990400643847312,"score_spread":0.2841648529017188,"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."}}