{"id":"W4417025273","doi":"10.1145/3756884.3768420","title":"Towards Generative and Expressive 3D Facial Animations","year":2025,"lang":"","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer facial animation; Animation; Leverage (statistics); Generative grammar; Facial motion capture; Motion capture; Generative model; Face (sociological concept)","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":[0.0006443553,0.0008278839,0.000429607,0.0005590752,0.0002783938,0.0009807845,0.0009200634,0.0007581696,0.007037343],"category_scores_gemma":[0.002227908,0.0007139743,0.00117352,0.0002611617,0.0007777209,0.0007156299,0.001773919,0.001334332,0.002274574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004000645,"about_ca_system_score_gemma":0.0003520073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001750079,"about_ca_topic_score_gemma":0.002605505,"domain_scores_codex":[0.9996669,0.00007748199,0.00001108693,0.00007378387,0.0001403693,0.00003036036],"domain_scores_gemma":[0.9996067,0.000197807,0.00002517019,0.0000819431,0.00005437659,0.00003414262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001750228,0.0001015657,0.001824423,0.0003439016,0.00008406829,0.0004508131,0.001095841,0.5667694,0.1020389,0.03542719,0.008551483,0.2831374],"study_design_scores_gemma":[0.00001256971,0.00004348939,0.0002821392,0.00003228952,0.00001005886,0.0001865577,0.00006063045,0.9733897,0.01048289,0.007517085,0.007965027,0.00001765937],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01005962,0.0001289584,0.9829391,0.0001228675,0.00005550074,0.00007939785,0.0001719437,0.002450308,0.003992341],"genre_scores_gemma":[0.3280395,0.0006255379,0.6555166,0.0003486248,0.00008654303,0.0002720441,0.001145491,0.001747916,0.01221774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007037343,"threshold_uncertainty_score":0.02354223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01887904822271981,"score_gpt":0.2806539770893186,"score_spread":0.2617749288665988,"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."}}