{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003302953,0.0001363496,0.0001841564,0.00004115096,0.00009985044,0.0001546671,0.000561334,0.00006070423,0.0001091433],"category_scores_gemma":[0.00006093928,0.0001090331,0.0001126885,0.0001525172,0.00002923909,0.0005683333,0.0001317632,0.00005764204,0.0002016209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002319005,"about_ca_system_score_gemma":0.00004672216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003517813,"about_ca_topic_score_gemma":0.00002762751,"domain_scores_codex":[0.9988642,0.00006428311,0.0001909436,0.0004224732,0.0001709457,0.0002871582],"domain_scores_gemma":[0.9990094,0.0002514535,0.00005687813,0.0005020337,0.0001007046,0.00007953341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005629414,0.0001415678,0.0004139304,0.0000121799,0.00008470988,0.000002177826,0.0007934289,0.02459285,0.01137452,0.6728323,0.03962854,0.2500676],"study_design_scores_gemma":[0.0008086103,0.0006898528,0.0007927938,0.00001231477,0.000009721979,0.000002899067,0.0002710501,0.9142279,0.01817554,0.003563409,0.06103522,0.0004107077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004868728,0.00001654427,0.9852974,0.0009131138,0.0008569346,0.0003035743,0.000005162757,0.0001248741,0.007613618],"genre_scores_gemma":[0.9403411,0.000005175919,0.05267712,0.0007606571,0.0002183717,0.00002090706,0.000005257559,0.000009576986,0.005961805],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9354724,"threshold_uncertainty_score":0.4446241,"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."}}