{"id":"W4404690192","doi":"10.1007/978-3-031-73030-6_25","title":"Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vector Institute; University of Toronto","funders":"","keywords":"Computer science; Rendering (computer graphics); Computer graphics (images); Computer vision; Inverse; Artificial intelligence; Geometry; Mathematics","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006075004,0.0006015638,0.0004880015,0.001644734,0.0002584243,0.001056476,0.002312424,0.0002798623,0.00001280203],"category_scores_gemma":[0.00003331213,0.0004980315,0.0001333377,0.001352392,0.0004506024,0.0005380256,0.001589396,0.0007300499,0.0000192978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003288519,"about_ca_system_score_gemma":0.0004845789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001095691,"about_ca_topic_score_gemma":0.0002673699,"domain_scores_codex":[0.9960798,0.00002704557,0.0005573656,0.001721603,0.001075908,0.0005383013],"domain_scores_gemma":[0.9976836,0.0002010057,0.0002465726,0.001387864,0.0002920368,0.0001889162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000148845,0.00007952851,0.00014419,0.0003117772,0.00005223425,0.0005651197,0.002352012,0.005220031,0.0004747825,0.7602863,0.0002988391,0.2302003],"study_design_scores_gemma":[0.00015854,0.0002248581,0.00005487574,0.0009494382,0.00001250935,0.0001231167,1.349587e-7,0.7499269,0.001340844,0.2447948,0.001788673,0.0006253204],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002339077,0.0001951091,0.9939231,0.0002233925,0.001176291,0.0004297223,0.000005360359,0.0007845773,0.003028493],"genre_scores_gemma":[0.4703252,0.0004062266,0.5231035,0.003585536,0.001020127,0.00007368153,0.0000481969,0.0002084412,0.001229023],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7447069,"threshold_uncertainty_score":0.9999805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02408917442695799,"score_gpt":0.27255958743458,"score_spread":0.248470413007622,"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."}}