{"id":"W4386065894","doi":"10.1109/cvpr52729.2023.00842","title":"Invertible Neural Skinning","year":2023,"lang":"en","type":"article","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Skinning; Computer science; Invertible matrix; Pipeline (software); Artificial intelligence; Differentiable function; Artificial neural network; Process (computing); Computer vision; Computer graphics (images); Programming language; Mathematics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003815955,0.00004059561,0.0000499915,0.00007939209,0.00002396771,0.00001525667,0.00004374974,0.00001631722,0.00009936345],"category_scores_gemma":[0.000004568194,0.00003643216,0.00003184763,0.0003259258,0.000003141677,0.00003650304,0.00001077657,0.00004174081,0.0006313883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005373718,"about_ca_system_score_gemma":0.000001236179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001316314,"about_ca_topic_score_gemma":0.000005170002,"domain_scores_codex":[0.9997181,0.000002223624,0.00005783149,0.00005169333,0.00005152183,0.0001186498],"domain_scores_gemma":[0.9998875,0.000008352857,0.000002013649,0.0000701574,0.000005700271,0.00002622175],"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":[1.38747e-7,8.088538e-7,0.0006160071,0.0000073533,0.00001361166,0.000004062356,0.00006590145,0.9796625,0.001370553,0.00007735321,0.01220989,0.005971828],"study_design_scores_gemma":[0.00002892039,0.000001467722,0.0001591336,0.000002364163,0.000003994591,3.833171e-7,0.00003296217,0.9981899,0.0009106821,0.0001795546,0.0004393547,0.00005125898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9115386,0.00009005393,0.03322107,0.0002952264,0.0002099997,0.00002093811,7.79019e-7,0.003633156,0.05099019],"genre_scores_gemma":[0.997381,0.00001485409,0.0001858226,0.00005815973,0.00003779981,0.000001726924,0.000004502951,0.000011296,0.002304858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08584239,"threshold_uncertainty_score":0.8115429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01658308381944026,"score_gpt":0.2094428961264937,"score_spread":0.1928598123070535,"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."}}