{"id":"W4404366881","doi":"10.18280/ts.410522","title":"Segmentation Guided Attention Networks for Human Pose Estimation","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Segmentation; Artificial intelligence; Pose; Estimation; Computer vision; Pattern recognition (psychology); Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003005245,0.0001058735,0.00007664819,0.0001368667,0.0002129831,0.0004152056,0.0001382073,0.00004182801,0.000184952],"category_scores_gemma":[0.000002973938,0.0001045813,0.00008841945,0.0001647783,0.00001205476,0.0008029682,0.00002098179,0.00005907216,0.00005985655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007151742,"about_ca_system_score_gemma":0.00001784018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005495581,"about_ca_topic_score_gemma":0.000003519162,"domain_scores_codex":[0.9990645,0.00003498352,0.0002728628,0.0002762229,0.0001868671,0.0001645304],"domain_scores_gemma":[0.9996913,0.0000429562,0.00005791902,0.00009836567,0.00006489486,0.00004457639],"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":[0.00001723867,0.0002256505,0.00007001973,0.0002027137,0.0001300183,0.00001326682,0.0007702617,0.01517537,0.06886015,0.1216369,0.0351197,0.7577787],"study_design_scores_gemma":[0.0004788863,0.0001639496,0.0008886989,0.00007819525,0.00003245778,0.000008875514,0.00001882041,0.9830005,0.003492703,0.009699421,0.001980863,0.0001566783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03995174,0.00004368571,0.9579108,0.0004352637,0.0005269993,0.0004425677,0.000005028299,0.0003205267,0.0003633355],"genre_scores_gemma":[0.9843503,0.000005018294,0.01425507,0.0002400194,0.0004029815,0.0001489235,0.0002674208,0.00001119811,0.0003191281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9678251,"threshold_uncertainty_score":0.42647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03326863533911979,"score_gpt":0.3050309123566629,"score_spread":0.2717622770175431,"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."}}