{"id":"W4236565392","doi":"10.1145/2070781.2024196","title":"Artist friendly facial animation retargeting","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Human Motion and Animation","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Retargeting; Computer science; Animation; Computer facial animation; Key frame; Computer graphics (images); Workflow; Key (lock); Facial motion capture; Artificial intelligence; Computer animation; Computer vision; Character animation; Process (computing); Set (abstract data type); Human–computer interaction; Frame (networking); Facial recognition system; Pattern recognition (psychology); Programming language","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":[0.00008333589,0.0001074823,0.00007814256,0.0001738194,0.0001746071,0.00002315345,0.000107907,0.00008071059,0.0005524066],"category_scores_gemma":[0.00001150157,0.0001193716,0.00007131806,0.0002389926,0.00002907325,0.0002048782,0.000001013305,0.0002050579,0.0001657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002174392,"about_ca_system_score_gemma":0.000004788414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007129613,"about_ca_topic_score_gemma":0.00005386958,"domain_scores_codex":[0.9994159,0.00001764045,0.0001813835,0.0001158109,0.0001246959,0.0001445948],"domain_scores_gemma":[0.9996703,0.00001623204,0.00002189009,0.0002051333,0.00003227715,0.00005415755],"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":[0.0002859372,0.001896507,0.002496074,0.0008112252,0.001015587,0.00005647749,0.04250559,0.03369303,0.07726003,0.1352165,0.007835724,0.6969273],"study_design_scores_gemma":[0.005652435,0.002033977,0.2551824,0.0005362546,0.0004574065,0.00009315548,0.003435279,0.2918203,0.1932005,0.09163789,0.1508178,0.005132638],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1634409,0.00003142038,0.8204631,0.00008816263,0.0005175669,0.0001599152,0.0000265978,0.0009462265,0.01432612],"genre_scores_gemma":[0.9944166,0.00005962689,0.005319008,0.0000567298,0.0000302919,0.00001468278,0.00001094805,0.00002260805,0.00006950027],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8309757,"threshold_uncertainty_score":0.6048465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03137706771161896,"score_gpt":0.2219536627693051,"score_spread":0.1905765950576861,"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."}}