{"id":"W4386076278","doi":"10.1109/cvpr52729.2023.01207","title":"HumanGen: Generating Human Radiance Fields with Explicit Priors","year":2023,"lang":"en","type":"article","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Radiance; Prior probability; Computer science; Rendering (computer graphics); Generator (circuit theory); Artificial intelligence; Computer vision; Mesh generation; Representation (politics); Computer graphics (images); Finite element method","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":[0.0004489421,0.0008439167,0.0003689697,0.0003112775,0.0001734699,0.0007303147,0.0006954962,0.000574096,0.006760296],"category_scores_gemma":[0.001076803,0.000389522,0.0007447578,0.0002042218,0.0005554206,0.0005376647,0.001298168,0.0009701429,0.001688855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00030607,"about_ca_system_score_gemma":0.0003529971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006929243,"about_ca_topic_score_gemma":0.001682433,"domain_scores_codex":[0.9997866,0.00004620415,0.000005558303,0.00005429465,0.00008897763,0.00001830089],"domain_scores_gemma":[0.999759,0.00008493327,0.00001644868,0.00008267142,0.000030068,0.00002692817],"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":[0.000427981,0.0001702521,0.001445969,0.0003395092,0.0001234692,0.0004903706,0.0004431955,0.3888357,0.1674671,0.04089039,0.02590687,0.3734592],"study_design_scores_gemma":[0.00005862909,0.0001382714,0.0005073105,0.00003623927,0.0000251883,0.0005691228,0.00004922185,0.9078532,0.04995739,0.01413533,0.02660853,0.00006149464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007379468,0.0001522663,0.9854322,0.0001027925,0.00007361214,0.00005496783,0.0001619258,0.002526117,0.004116657],"genre_scores_gemma":[0.2923967,0.0003680876,0.6910999,0.0004888562,0.00006867143,0.0001822079,0.0009700173,0.002476294,0.01194926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006760296,"threshold_uncertainty_score":0.02261543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01831309204665187,"score_gpt":0.2239681183422669,"score_spread":0.2056550262956151,"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."}}