{"id":"W4390946825","doi":"10.1145/3641107","title":"GANonymization: A GAN-Based Face Anonymization Framework for Preserving Emotional Expressions","year":2024,"lang":"en","type":"article","venue":"ACM Transactions on Multimedia Computing Communications and Applications","topic":"Face recognition and analysis","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Leibniz-Gemeinschaft; Deutsche Forschungsgemeinschaft","keywords":"Computer science; Facial expression; Anonymity; Face (sociological concept); Representation (politics); Expression (computer science); Adversarial system; Artificial intelligence; Pattern recognition (psychology); Computer security","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0003083768,0.0002415154,0.0002106439,0.0004416149,0.001548908,0.0005257727,0.00159217,0.0001529817,0.00006427304],"category_scores_gemma":[0.0001221478,0.0002485958,0.0001834555,0.001405823,0.0001508361,0.0003778935,0.00006299911,0.0003923082,0.00005175031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006355747,"about_ca_system_score_gemma":0.0001626348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001010798,"about_ca_topic_score_gemma":0.000008030541,"domain_scores_codex":[0.9982577,0.0001348019,0.0004577415,0.0006251014,0.0002468442,0.0002777908],"domain_scores_gemma":[0.9938615,0.003426014,0.0001134837,0.002156676,0.0002671291,0.000175186],"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":[0.000007574901,0.000768615,0.00005612085,0.0001908629,0.0001739209,5.756661e-7,0.001157463,0.05768857,0.001208018,0.09544374,0.0003337204,0.8429708],"study_design_scores_gemma":[0.000262124,0.00003530449,0.00009342872,0.0002922329,0.00006415886,0.000004494639,0.0001087406,0.9640357,0.0007218934,0.01253232,0.02158282,0.0002667626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000595427,0.0006467688,0.9851561,0.01187515,0.0001312031,0.0008857141,0.0001137801,0.0007636013,0.0003681175],"genre_scores_gemma":[0.3991494,0.0003204119,0.5991641,0.0003088231,0.00007029987,0.0006552663,0.0001761076,0.00002604718,0.000129458],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9063472,"threshold_uncertainty_score":0.9999966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03609341277784488,"score_gpt":0.3231485393841007,"score_spread":0.2870551266062558,"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."}}