{"id":"W4405865448","doi":"10.1016/j.patcog.2024.111312","title":"Visual style prompt learning using diffusion models for blind face restoration","year":2024,"lang":"en","type":"article","venue":"Pattern Recognition","topic":"Face recognition and analysis","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Face (sociological concept); Style (visual arts); Computer science; Artificial intelligence; Computer vision; Diffusion; 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":[0.0003221204,0.0001507043,0.0001436502,0.0003022337,0.0002296253,0.0005426022,0.0001370573,0.00009035545,0.00004749793],"category_scores_gemma":[0.00003388673,0.0001481401,0.0001327425,0.0004057268,0.00001453516,0.001181987,0.00006471937,0.0001697819,0.0001631001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007845287,"about_ca_system_score_gemma":0.00004347971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003237667,"about_ca_topic_score_gemma":0.00001507276,"domain_scores_codex":[0.9986892,0.000101377,0.0002565721,0.000470699,0.0002518351,0.0002303501],"domain_scores_gemma":[0.999483,0.00009708858,0.00008237767,0.0001144128,0.0001512429,0.0000718813],"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":[0.00001310318,0.00007745669,0.00005142004,0.0001396692,0.00003812471,0.000006162707,0.00093768,0.002736052,0.01071127,0.0000442613,0.00008288566,0.9851619],"study_design_scores_gemma":[0.0003594678,0.00009196676,0.00002094749,0.0002239961,0.00004382798,0.00001023115,0.0001416907,0.9917688,0.004041876,0.002790424,0.0002924275,0.0002143718],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2226796,0.00009014204,0.7760403,0.0002675527,0.0002576731,0.000276873,0.00001325059,0.0002736699,0.0001009836],"genre_scores_gemma":[0.9897588,0.00004613988,0.009360647,0.0001203368,0.0001822863,0.00007092575,0.0002521271,0.00002292694,0.0001858398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9890327,"threshold_uncertainty_score":0.6040977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07670839348405505,"score_gpt":0.3195823727647708,"score_spread":0.2428739792807157,"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."}}