{"id":"W3199806759","doi":"10.1134/s1054661821030123","title":"Identity-Preserved Face Beauty Transformation with Conditional Generative Adversarial Networks","year":2021,"lang":"en","type":"article","venue":"Pattern Recognition and Image Analysis","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Beauty; Normalization (sociology); Computer science; Discriminator; Artificial intelligence; Face (sociological concept); Identity (music); Pattern recognition (psychology); Computer vision; Mathematics; Aesthetics; Art; Linguistics","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":[0.000255433,0.000200107,0.0003131065,0.0001820829,0.0003031725,0.0006543467,0.0001984393,0.00007027869,0.0004350072],"category_scores_gemma":[0.000033252,0.0001794224,0.0001912026,0.001055742,0.0000730074,0.002669767,0.00008826332,0.0001514926,0.00003706201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002906795,"about_ca_system_score_gemma":0.00004432629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009920754,"about_ca_topic_score_gemma":0.0005828916,"domain_scores_codex":[0.9983124,0.0003038073,0.000299298,0.0004947397,0.0003211873,0.0002685706],"domain_scores_gemma":[0.9989418,0.0000873063,0.000138466,0.0002617216,0.0004355968,0.0001350815],"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":[0.0003381454,0.001545068,0.01935738,0.0002068437,0.02109253,0.0008395128,0.01128093,0.1926847,0.02031641,0.001842619,0.004029589,0.7264663],"study_design_scores_gemma":[0.00112654,0.00006732551,0.01219872,0.00002101331,0.0008865902,0.00002056828,0.0003883796,0.9735162,0.009279227,0.001872116,0.0002066951,0.0004166088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01195053,0.000123647,0.9858862,0.00119531,0.00009635829,0.0001231713,0.00009601792,0.00005270878,0.0004760396],"genre_scores_gemma":[0.9749311,0.000200492,0.02209998,0.00103412,0.0002002069,0.00003089099,0.00141966,0.000009724379,0.00007388192],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9637862,"threshold_uncertainty_score":0.7316634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02052871819918349,"score_gpt":0.2368321409592417,"score_spread":0.2163034227600582,"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."}}