{"id":"W2987290548","doi":"10.1109/mmsp.2019.8901744","title":"Virtual Fakes: DeepFakes for Virtual Reality","year":2019,"lang":"en","type":"article","venue":"","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Virtual reality; Computer science; Face (sociological concept); Human–computer interaction; Artificial intelligence; Computer graphics (images); Computer vision; Multimedia","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":[0.001358723,0.0007283901,0.0005067649,0.0004310372,0.0004453555,0.0009830943,0.0008178042,0.001239706,0.004154793],"category_scores_gemma":[0.00862975,0.0003277542,0.0004598724,0.0002321183,0.001204947,0.001460938,0.001612926,0.001803068,0.000609813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006973599,"about_ca_system_score_gemma":0.0003302314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008679893,"about_ca_topic_score_gemma":0.001155548,"domain_scores_codex":[0.9990408,0.0003632972,0.00002865577,0.0001385293,0.0003152025,0.0001133628],"domain_scores_gemma":[0.9969812,0.001801749,0.0002536245,0.0006769237,0.0001893331,0.00009718892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008146075,0.0002324181,0.003051033,0.0003289536,0.000173527,0.0006099832,0.0003399545,0.6783566,0.03233633,0.07217418,0.01355589,0.1980265],"study_design_scores_gemma":[0.00002460631,0.0001380503,0.0006907835,0.00002994461,0.00001724631,0.0002924404,0.00002872399,0.9693425,0.009996978,0.01655918,0.002858144,0.00002134889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1898276,0.001058244,0.7910627,0.001946682,0.0004469501,0.0002146072,0.0005282803,0.001918985,0.01299594],"genre_scores_gemma":[0.9518982,0.0001635721,0.04424665,0.0002590527,0.00004000612,0.00005401432,0.0002058203,0.00008576209,0.003046818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004154793,"threshold_uncertainty_score":0.01389921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01909796822468483,"score_gpt":0.2469705889331311,"score_spread":0.2278726207084463,"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."}}