{"id":"W4393158999","doi":"10.1609/aaai.v38i3.27960","title":"PoseGen: Learning to Generate 3D Human Pose Dataset with NeRF","year":2024,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Artificial intelligence; Computer science","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":[0.001772892,0.002753546,0.001290774,0.001376672,0.0004787719,0.0009037193,0.003574979,0.002073585,0.01043438],"category_scores_gemma":[0.005704587,0.001076736,0.001944167,0.0008549731,0.0009747768,0.001851943,0.003063379,0.002778126,0.007305637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009365858,"about_ca_system_score_gemma":0.001002361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004931027,"about_ca_topic_score_gemma":0.01026873,"domain_scores_codex":[0.998793,0.0002100947,0.00003949411,0.0005492027,0.0003120681,0.00009609639],"domain_scores_gemma":[0.9988763,0.0003654897,0.00006995079,0.0004175349,0.0001843041,0.00008644041],"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":[0.0006198534,0.0006357886,0.004224464,0.0004400255,0.0002477737,0.0003825645,0.0002269934,0.2281317,0.01308212,0.005492119,0.07329872,0.673218],"study_design_scores_gemma":[0.0001030075,0.0002606673,0.001293702,0.00005384702,0.00002338003,0.0004006462,0.00007011678,0.9574038,0.0108316,0.01255798,0.01693623,0.00006503496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01016151,0.000529538,0.9380453,0.0002868327,0.0002571802,0.0004130809,0.00461321,0.04368559,0.002007807],"genre_scores_gemma":[0.1417813,0.0003975351,0.8155773,0.001045152,0.0001190395,0.001139866,0.0327888,0.002244452,0.004906489],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01043438,"threshold_uncertainty_score":0.03490651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07217025472238092,"score_gpt":0.3118457125422451,"score_spread":0.2396754578198642,"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."}}