{"id":"W3008728787","doi":"10.1007/s11263-020-01300-7","title":"Layout2image: Image Generation from Layout","year":2020,"lang":"en","type":"article","venue":"International Journal of Computer Vision","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada; Vector Institute; University of British Columbia; Business Development Bank of Canada; Royal Bank of Canada","funders":"","keywords":"Computer science; Artificial intelligence; Bounding overwatch; Embedding; Set (abstract data type); Pattern recognition (psychology); Image (mathematics); Object (grammar); Generative model; Representation (politics); Boosting (machine learning); Generative grammar","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":[0.0004653277,0.001429253,0.0006247628,0.0009538303,0.0002828815,0.0008425809,0.001737627,0.001704223,0.0226877],"category_scores_gemma":[0.001989457,0.0008630102,0.0009031306,0.000530044,0.0004720265,0.0006847999,0.001828433,0.001335997,0.006518576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005453234,"about_ca_system_score_gemma":0.0005848221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001548099,"about_ca_topic_score_gemma":0.002735096,"domain_scores_codex":[0.9996972,0.00004595237,0.000008786169,0.00008913623,0.0001195055,0.00003938841],"domain_scores_gemma":[0.9995918,0.0001457824,0.00002385618,0.0001349852,0.00007109409,0.00003250154],"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":[0.0006514859,0.0002195445,0.001080213,0.0004460281,0.0002037604,0.0006413528,0.0001639855,0.2843306,0.08111466,0.0206157,0.07038367,0.540149],"study_design_scores_gemma":[0.00009627776,0.00007462074,0.0001865861,0.0000166415,0.00001837576,0.0002398501,0.00001557301,0.942748,0.03810589,0.00801852,0.0104559,0.00002384197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005546592,0.0001396725,0.9603974,0.0001819471,0.0001942242,0.0001477807,0.0007337225,0.02971037,0.002948225],"genre_scores_gemma":[0.1592391,0.0001827798,0.817781,0.000370803,0.00009832255,0.0003423746,0.002777006,0.008779669,0.01042894],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0226877,"threshold_uncertainty_score":0.07589793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01976551630966746,"score_gpt":0.2679329790610798,"score_spread":0.2481674627514124,"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."}}