{"id":"W4390872712","doi":"10.1109/iccv51070.2023.01384","title":"Dynamic Mesh Recovery from Partial Point Cloud Sequence","year":2023,"lang":"en","type":"article","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Prior probability; Computer science; Autoencoder; Artificial intelligence; Point cloud; Computer vision; Transformer; Pattern recognition (psychology); Deep learning; Bayesian probability","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":[0.000397652,0.000748412,0.0009028715,0.0009392971,0.0002811151,0.0005038269,0.0009319094,0.001180758,0.001807642],"category_scores_gemma":[0.002105724,0.0006185265,0.0008033296,0.0009207412,0.000664486,0.001000628,0.001308161,0.001425838,0.0006447984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004597352,"about_ca_system_score_gemma":0.0008026876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004518816,"about_ca_topic_score_gemma":0.005723538,"domain_scores_codex":[0.9997281,0.000027673,0.0000121751,0.00007474574,0.0001155585,0.00004163383],"domain_scores_gemma":[0.9995289,0.0001390155,0.00005194822,0.000150754,0.00009397174,0.00003535065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001805342,0.00004839104,0.001643937,0.0001154665,0.00005182257,0.0002939391,0.0001085676,0.7831165,0.02819786,0.00876693,0.003231176,0.1742449],"study_design_scores_gemma":[0.000003677074,0.00001248454,0.0002814499,0.000006256883,0.000002757476,0.00005008168,0.00001320299,0.9937997,0.00238323,0.002923018,0.0005179768,0.000006182395],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03632878,0.0001525599,0.9615397,0.0001478884,0.0000460806,0.00003556587,0.00023854,0.0007202446,0.0007906859],"genre_scores_gemma":[0.6895785,0.0003825374,0.3043967,0.0001631811,0.00005171914,0.00009567275,0.001802429,0.0002669502,0.003262318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004518816,"threshold_uncertainty_score":0.008984983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01800334563807402,"score_gpt":0.2338630377426028,"score_spread":0.2158596921045288,"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."}}