{"id":"W4387999334","doi":"10.1145/3630750","title":"Intrinsic Image Decomposition via Ordinal Shading","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Shading; Computer science; Rendering (computer graphics); Algorithm; Decomposition; Artificial intelligence; Generalization; Computer vision; Albedo (alchemy); Mathematics; Computer graphics (images)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006117538,0.0007135791,0.0004430497,0.0006338781,0.0002399695,0.001069035,0.0009089945,0.0006209071,0.002401876],"category_scores_gemma":[0.001917548,0.0003626127,0.0005763659,0.0004106999,0.0007154878,0.001697414,0.001477943,0.001574336,0.0007334967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000617271,"about_ca_system_score_gemma":0.0006392514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001836491,"about_ca_topic_score_gemma":0.00271098,"domain_scores_codex":[0.9996697,0.00007187828,0.00001143944,0.00006323648,0.0001470065,0.00003667656],"domain_scores_gemma":[0.9994847,0.0001361674,0.0000647761,0.000143073,0.0001251008,0.00004620082],"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":[0.00009984749,0.0000560356,0.001476508,0.0001460174,0.00004563851,0.0001026965,0.0001829601,0.7407827,0.03354939,0.08120787,0.003677497,0.1386728],"study_design_scores_gemma":[0.000002789534,0.00001324222,0.0001836398,0.000005725773,0.000003003413,0.00002846001,0.00001102793,0.9820338,0.002127966,0.01445757,0.001126549,0.000006097036],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0105018,0.00004443874,0.9878528,0.00007976928,0.00001172495,0.00001070298,0.00007089307,0.00027493,0.001152989],"genre_scores_gemma":[0.5078585,0.0002676106,0.4850896,0.0001811019,0.00006272046,0.0000868702,0.0006685252,0.000443991,0.005341104],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002401876,"threshold_uncertainty_score":0.008035123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02027504969118586,"score_gpt":0.3099234596397862,"score_spread":0.2896484099486003,"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."}}