{"id":"W4367662933","doi":"10.1109/vrw58643.2023.00244","title":"F2RPC: Fake to Real Portrait Control from a Virtual Character","year":2023,"lang":"en","type":"article","venue":"","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"National Research Foundation of Korea","keywords":"Portrait; Computer science; Character (mathematics); Task (project management); Artificial intelligence; Virtual reality; Face (sociological concept); Computer graphics (images); Computer vision; Image (mathematics); Motion (physics); Human–computer interaction; Art; Visual arts; Mathematics; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002052535,0.000137942,0.0001954899,0.00008810991,0.00009437672,0.0001851924,0.0005261638,0.0000501843,0.0002515774],"category_scores_gemma":[0.00003975598,0.0001126009,0.000081859,0.0004288251,0.00001698247,0.0003494563,0.0001774515,0.00007215264,0.001743112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001598933,"about_ca_system_score_gemma":0.00004001067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004601457,"about_ca_topic_score_gemma":0.000110944,"domain_scores_codex":[0.9987429,0.00006548257,0.0001947456,0.0004327284,0.0002275157,0.0003366591],"domain_scores_gemma":[0.9991606,0.0001565447,0.00003876507,0.0004151337,0.00005814956,0.0001708303],"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":[0.0001089699,0.0001839083,0.003178977,0.000003788671,0.000350554,0.0003333473,0.003452284,0.007725859,0.1509026,0.07729077,0.287948,0.4685209],"study_design_scores_gemma":[0.001791426,0.000436402,0.3057186,0.00002824621,0.00003194282,0.000004349631,0.0001856564,0.5664133,0.008678591,0.00303255,0.1126916,0.0009873905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03795052,0.000004279595,0.9442914,0.008007853,0.000790834,0.0002032839,0.00002931579,0.0004265717,0.008295946],"genre_scores_gemma":[0.9792631,0.000008823257,0.01113218,0.003178324,0.0005380422,0.00002597374,0.00001230409,0.00001110685,0.005830193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9413126,"threshold_uncertainty_score":0.9990342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01193717505343872,"score_gpt":0.2255630080263195,"score_spread":0.2136258329728808,"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."}}