{"id":"W2509413994","doi":"10.1111/cgf.12976","title":"Learning 3D Scene Synthesis from Annotated RGB‐D Images","year":2016,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Object (grammar); Artificial intelligence; RGB color model; Probabilistic logic; Computer vision; Task (project management); Controllability; Scale (ratio); Pattern recognition (psychology); Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006123976,0.001401578,0.0008810712,0.001311622,0.0002799303,0.0009550024,0.001425481,0.0008693964,0.003348679],"category_scores_gemma":[0.001588249,0.001028868,0.001646918,0.0009542752,0.0005724017,0.001031642,0.001180514,0.0009134223,0.001370549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008074463,"about_ca_system_score_gemma":0.00076909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003317173,"about_ca_topic_score_gemma":0.006272066,"domain_scores_codex":[0.9994534,0.00007233144,0.00002524484,0.0002535831,0.0001485864,0.00004694231],"domain_scores_gemma":[0.9993542,0.0002551188,0.00006728003,0.0001620221,0.0001200501,0.00004133374],"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":[0.0003432988,0.0001827884,0.002377595,0.0003237399,0.0001707363,0.0001762011,0.0001743455,0.4580184,0.06177956,0.00356109,0.004034543,0.4688578],"study_design_scores_gemma":[0.00001879329,0.00006735825,0.0005173086,0.00001290451,0.00001955516,0.00005178527,0.00004596321,0.976303,0.01830835,0.002667556,0.001971747,0.0000156904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02984492,0.0001551062,0.9628156,0.00006427437,0.00003898214,0.00008736646,0.000515984,0.005361114,0.001116519],"genre_scores_gemma":[0.2806181,0.0002034933,0.71465,0.0001192786,0.00003210384,0.0001455099,0.00223734,0.0004897055,0.00150443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003348679,"threshold_uncertainty_score":0.01120245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009598763711390167,"score_gpt":0.2350676439399857,"score_spread":0.2254688802285956,"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."}}