{"id":"W4401017512","doi":"10.1109/tvcg.2024.3434386","title":"FACEMUG: A Multimodal Generative and Fusion Framework for Local Facial Editing","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Image editing; Artificial intelligence; Feature (linguistics); Generative grammar; Generative model; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007774342,0.001042783,0.0006456379,0.0007705894,0.0003831743,0.0009564019,0.001408257,0.0007162279,0.005739921],"category_scores_gemma":[0.001665797,0.0003908828,0.001282843,0.0004638682,0.0008164397,0.001025217,0.00189147,0.00136816,0.001138398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000465582,"about_ca_system_score_gemma":0.000463377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002133489,"about_ca_topic_score_gemma":0.00350935,"domain_scores_codex":[0.9994422,0.0001198262,0.00001797371,0.0001363453,0.0002296804,0.00005400895],"domain_scores_gemma":[0.9996114,0.0001254853,0.00003569646,0.0001328087,0.00005632817,0.00003815891],"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":[0.0002350953,0.0001303251,0.0009519579,0.0002446484,0.0001760144,0.000400149,0.0005739746,0.2642151,0.1143643,0.03317154,0.008508654,0.5770282],"study_design_scores_gemma":[0.0000213187,0.00007698908,0.0004356909,0.00002065255,0.00003733743,0.0003626239,0.00006822922,0.9463446,0.02658868,0.01560784,0.01038838,0.00004755433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003688256,0.0001436119,0.993437,0.0000459938,0.00002721791,0.00003717612,0.0000525428,0.001343015,0.001225138],"genre_scores_gemma":[0.277134,0.0004547873,0.7117791,0.0002305557,0.00008785701,0.0001994836,0.0004667141,0.001249695,0.008398002],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005739921,"threshold_uncertainty_score":0.01920199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01948815635380958,"score_gpt":0.2846601965708095,"score_spread":0.2651720402169999,"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."}}