{"id":"W4413147181","doi":"10.1109/cvpr52734.2025.01667","title":"Exposure-slot: Exposure-centric representations learning with Slot-in-Slot Attention for Region-aware Exposure Correction","year":2025,"lang":"en","type":"article","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Artificial intelligence; Human–computer interaction","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":[0.0005820692,0.001016776,0.001115648,0.0007229652,0.0002914706,0.0008298105,0.001873259,0.001026759,0.003054127],"category_scores_gemma":[0.002113147,0.0003997914,0.0009179002,0.0007114236,0.0005903274,0.001573289,0.001807431,0.001516931,0.001238725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000584476,"about_ca_system_score_gemma":0.0008261407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002539881,"about_ca_topic_score_gemma":0.004577183,"domain_scores_codex":[0.9995658,0.0000557359,0.00001697006,0.0001671434,0.0001304078,0.00006408528],"domain_scores_gemma":[0.9994358,0.000140961,0.00005670248,0.0001902839,0.0001341129,0.00004197575],"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":[0.000396251,0.0001817063,0.001391401,0.0001939138,0.0001263106,0.0001217851,0.0001749416,0.05520103,0.0642071,0.003478837,0.01071322,0.8638135],"study_design_scores_gemma":[0.00005292509,0.000287151,0.001608231,0.00003365391,0.00009328262,0.000360545,0.00008363689,0.9284535,0.04855227,0.01016136,0.01025736,0.00005613097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01546576,0.0007051819,0.9769372,0.0001652817,0.0001299008,0.00007101067,0.0001937978,0.005254667,0.001077185],"genre_scores_gemma":[0.3978306,0.001002076,0.5876558,0.0008519235,0.0002256986,0.0002027373,0.001617882,0.001145271,0.009467952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003054127,"threshold_uncertainty_score":0.01021701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007686615925241603,"score_gpt":0.2246073211954863,"score_spread":0.2169207052702447,"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."}}