{"id":"W3011628670","doi":"10.1109/access.2020.2982224","title":"A State-of-the-Art Review on Image Synthesis With Generative Adversarial Networks","year":2020,"lang":"en","type":"review","venue":"IEEE Access","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":197,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Computer science; Inpainting; Image synthesis; Artificial intelligence; Image (mathematics); Image translation; Field (mathematics); Face (sociological concept); Generative grammar; Computer vision; Adversarial system; Image editing; Animation; Translation (biology); Image processing; Generative adversarial network; Computer graphics (images)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004616615,0.000855623,0.002750343,0.0001155744,0.0002328035,0.0004160391,0.004553769,0.0001700671,0.0000493226],"category_scores_gemma":[0.000234383,0.0004907376,0.0008750493,0.001771931,0.0002005418,0.0008139515,0.0007108423,0.000707706,0.0000850018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001278981,"about_ca_system_score_gemma":0.0006293913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001832275,"about_ca_topic_score_gemma":0.00001908059,"domain_scores_codex":[0.9954578,0.001198424,0.0009674354,0.001158596,0.0006881568,0.0005295723],"domain_scores_gemma":[0.9958207,0.0008254733,0.001287008,0.001626209,0.0002474387,0.0001931466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001306602,0.00005071706,3.432561e-7,0.004997951,0.0003734677,0.00004778206,0.00002205573,0.001373127,6.583153e-7,0.00007060847,0.03564181,0.9574084],"study_design_scores_gemma":[0.0001486883,0.0001158715,9.491361e-7,0.04497858,0.0009213584,0.00001983145,6.122604e-7,0.005145506,0.00018878,0.0000390495,0.947742,0.0006987536],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[4.601419e-8,0.6451137,0.3513959,0.0003932458,0.00103166,0.00126957,0.00003830481,0.0000520177,0.0007055957],"genre_scores_gemma":[0.0000155911,0.9918437,0.005753626,0.001054045,0.0007209441,0.0003588336,0.000009371855,0.00007585179,0.0001680482],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9567097,"threshold_uncertainty_score":0.9997544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03582565278061781,"score_gpt":0.3043865334228568,"score_spread":0.2685608806422389,"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."}}