{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005255528,0.00163835,0.0008869607,0.0009215416,0.0003434476,0.0005598203,0.001546397,0.001138113,0.002816221],"category_scores_gemma":[0.001790168,0.0006196293,0.0006717994,0.0007973086,0.0005892346,0.001281115,0.0009833557,0.001239879,0.0008575611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001262269,"about_ca_system_score_gemma":0.0008613987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01539729,"about_ca_topic_score_gemma":0.01977496,"domain_scores_codex":[0.9996487,0.0000601373,0.000009745635,0.0001355918,0.00006979336,0.00007602024],"domain_scores_gemma":[0.9995789,0.000173571,0.000053854,0.00005616676,0.0001029424,0.00003451014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000458957,0.0001570123,0.001788152,0.0001174117,0.0001322521,0.0001744527,0.0001108747,0.5446803,0.02060585,0.004449491,0.00784528,0.41948],"study_design_scores_gemma":[0.000005084042,0.00003008296,0.0004344276,0.000006336045,0.0000127815,0.00002711909,0.000008277452,0.9932174,0.00250729,0.003266745,0.0004783439,0.000006086102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05938658,0.001869022,0.9286005,0.0004839609,0.0001522787,0.00006362153,0.0003981578,0.005380237,0.003665628],"genre_scores_gemma":[0.872686,0.0009397372,0.1158787,0.0005402554,0.0002052568,0.0001023456,0.001229009,0.0002761779,0.008142453],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01539729,"threshold_uncertainty_score":0.03061533,"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."}}