{"id":"W2104425538","doi":"10.1145/1778765.1778778","title":"High resolution passive facial performance capture","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Face recognition and analysis","field":"Computer Science","cited_by":235,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Polygon mesh; Computer vision; Artificial intelligence; Texture mapping; Computer graphics (images); Face (sociological concept); Parameterized complexity; Sequence (biology); Tracking (education); Texture (cosmology); Image (mathematics); Algorithm","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":[0.0000983091,0.0001312409,0.0001175274,0.0002979045,0.0004114866,0.00008710688,0.0005767486,0.0001528185,0.00010745],"category_scores_gemma":[0.00002050023,0.0001214169,0.0001472595,0.0008566066,0.00007816024,0.0004028521,0.000007796573,0.0006170774,0.0001184292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001294211,"about_ca_system_score_gemma":0.00004179402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005328163,"about_ca_topic_score_gemma":0.0002968005,"domain_scores_codex":[0.9990377,0.0000309456,0.0001571054,0.00029319,0.0002703059,0.0002107961],"domain_scores_gemma":[0.9990206,0.00005767354,0.00005401778,0.0006464583,0.0001214067,0.00009984172],"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":[0.00004990057,0.0007698888,0.0004491383,0.00004516664,0.0002529369,0.00002067132,0.001264661,0.004609,0.009912759,0.04976893,0.001234147,0.9316228],"study_design_scores_gemma":[0.006515574,0.001404807,0.04907142,0.0002767954,0.0006728517,0.0002891775,0.0006075072,0.5953739,0.1460139,0.09343466,0.1017091,0.004630252],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1256263,0.000008923524,0.8678316,0.004940809,0.0009766587,0.00009565872,0.00002408248,0.0002429334,0.0002531006],"genre_scores_gemma":[0.9817482,0.0001384522,0.01714866,0.0006724086,0.00004221008,0.00002153808,0.00000784474,0.000007261941,0.0002134378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9269925,"threshold_uncertainty_score":0.4951237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01178120293641957,"score_gpt":0.2217284316932933,"score_spread":0.2099472287568737,"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."}}