{"id":"W4386071615","doi":"10.1109/cvpr52729.2023.01598","title":"Computational Flash Photography through Intrinsics","year":2023,"lang":"en","type":"article","venue":"","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Flash (photography); Intrinsics; Computer science; Computational photography; Photography; Computer graphics (images); Computer vision; Artificial intelligence; Image processing; Optics; Image (mathematics); Visual arts","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001415985,0.00007784662,0.00007078306,0.0001233809,0.00007100482,0.0001066332,0.0005154974,0.00002584104,0.00004326915],"category_scores_gemma":[0.00001072698,0.00007273436,0.00004531167,0.00122365,0.00003536954,0.0005221313,0.0002848839,0.00006212627,0.0007976437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001233729,"about_ca_system_score_gemma":0.00002433414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007384258,"about_ca_topic_score_gemma":0.000001327283,"domain_scores_codex":[0.9991655,0.00001847929,0.0001261872,0.0002265182,0.0002628398,0.0002004366],"domain_scores_gemma":[0.9995508,0.00006158625,0.0000280224,0.0002677791,0.00006700703,0.00002484656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000001334479,0.00004412722,0.0002582395,0.000009396074,0.00001885942,0.00002423289,0.0007842862,0.0003371903,0.000853807,0.59354,0.3663767,0.03775187],"study_design_scores_gemma":[0.0003696217,0.0001142779,0.00212079,0.00001902661,0.000003426157,0.00000851356,0.00002819546,0.2127305,0.07392655,0.5490053,0.1612453,0.0004285698],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001645313,0.000009825814,0.9446493,0.0006080503,0.0001778722,0.000113508,7.983945e-7,0.002551805,0.0502435],"genre_scores_gemma":[0.1875927,0.00002228412,0.8092332,0.001065696,0.00004263513,0.00003709493,0.00001104585,0.000008919709,0.001986328],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2123933,"threshold_uncertainty_score":0.9999803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01851658604242543,"score_gpt":0.2766200847689285,"score_spread":0.2581034987265031,"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."}}