{"id":"W4312999101","doi":"10.1109/cvpr52688.2022.01694","title":"Modeling sRGB Camera Noise with Normalizing Flows","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; York University","funders":"","keywords":"Computer science; RGB color model; Noise (video); Artificial intelligence; Computer vision; Noise reduction; Dark-frame subtraction; Noise measurement; Image noise; Image sensor; Image (mathematics); Image processing; Median filter","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"],"consensus_categories":[],"category_scores_codex":[0.0007829636,0.0003948205,0.0004282214,0.0003782012,0.0008522646,0.0007529454,0.0007206335,0.0000733914,0.000502139],"category_scores_gemma":[0.000007235757,0.0003528712,0.0001110689,0.0004581829,0.00004386381,0.0007130777,0.0005003018,0.0006858334,0.0001008419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006252555,"about_ca_system_score_gemma":0.0001009065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001280333,"about_ca_topic_score_gemma":0.00002034647,"domain_scores_codex":[0.9966258,0.0006579093,0.0004605166,0.0009759516,0.0007905284,0.0004893136],"domain_scores_gemma":[0.9986582,0.0001528685,0.0001632031,0.0005533758,0.0002423813,0.0002299032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001602522,0.0002157859,0.00009023429,0.0000458068,0.00004048411,0.0002678384,0.001328942,0.009406931,0.002523863,0.000185007,0.001111345,0.9846235],"study_design_scores_gemma":[0.001513212,0.001168517,0.0001078403,0.0001724402,0.00001927435,0.0002487586,0.00009854657,0.9935282,0.0007172971,0.001071324,0.0007826729,0.0005719206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1719474,0.00005520867,0.8249233,0.0008893505,0.0009519245,0.0002738324,0.0000313079,0.0002023043,0.000725326],"genre_scores_gemma":[0.9447778,0.00008452756,0.04795914,0.006574661,0.0002539124,0.00008755623,0.00007540453,0.00003911207,0.0001478437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9841213,"threshold_uncertainty_score":0.9998924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05232009435441503,"score_gpt":0.2808313286522276,"score_spread":0.2285112342978126,"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."}}