{"id":"W2776622059","doi":"10.1109/iccv.2017.556","title":"3D Graph Neural Networks for RGBD Semantic Segmentation","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":525,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Unary operation; Computer science; Segmentation; Artificial intelligence; Point cloud; Pattern recognition (psychology); Graph; Representation (politics); Theoretical computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007766511,0.00009861248,0.00009062616,0.00003004135,0.000704144,0.0002729339,0.0009515956,0.00003272416,0.000005429544],"category_scores_gemma":[0.00001540222,0.00008849016,0.00005533196,0.00007874023,0.00004741601,0.000755722,0.0001861602,0.00006282829,0.00001074651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001195154,"about_ca_system_score_gemma":0.000007821553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007700201,"about_ca_topic_score_gemma":0.00003621618,"domain_scores_codex":[0.9991909,0.00001132984,0.0001426284,0.0003146235,0.00009585442,0.0002446878],"domain_scores_gemma":[0.9987601,0.00009285887,0.0001416486,0.0008924088,0.0000487821,0.00006416865],"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":[0.00001568753,0.00008135717,0.002209626,0.00001880459,0.0000283089,0.000005518781,0.0000849215,0.1106954,0.001439,0.2876986,0.01051656,0.5872061],"study_design_scores_gemma":[0.0002454822,0.00003206271,0.00252919,0.000002906786,0.000005199136,0.000004709604,0.000002779558,0.9845051,0.0005347228,0.01115049,0.0008649966,0.0001223594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002186734,0.00003029479,0.9938167,0.002079034,0.0003421033,0.0004476567,8.478986e-7,0.0001833712,0.0009132453],"genre_scores_gemma":[0.7665144,0.00001719437,0.2318545,0.0006448479,0.0001654805,0.0001350056,0.000006060008,0.00001005691,0.0006525155],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8738096,"threshold_uncertainty_score":0.5415777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02800042271662722,"score_gpt":0.3040027723263105,"score_spread":0.2760023496096833,"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."}}