{"id":"W2098535678","doi":"10.1145/1141911.1141956","title":"Removing camera shake from a single photograph","year":2006,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":1842,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Shake; Computer vision; Artificial intelligence; Camera auto-calibration; Computer science; Motion blur; Photography; Deconvolution; Digital camera; Blind deconvolution; Computer graphics (images); Rotation (mathematics); Image restoration; Pinhole camera model; Image (mathematics); Camera resectioning; Image processing; Physics; Algorithm; Art","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":[0.000370091,0.0008516107,0.00113778,0.0006731767,0.0008636947,0.0009674734,0.0007283835,0.001245819,0.006709101],"category_scores_gemma":[0.002467864,0.0005578096,0.0007424792,0.0006330006,0.0005833638,0.001240685,0.001254051,0.001240612,0.00292577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003758751,"about_ca_system_score_gemma":0.000646695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003022074,"about_ca_topic_score_gemma":0.004237412,"domain_scores_codex":[0.9995208,0.00003118713,0.00002198962,0.0001279279,0.0002051885,0.00009291047],"domain_scores_gemma":[0.9984958,0.0002887915,0.00008649298,0.0007229602,0.0003216643,0.00008424059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001375959,0.0002984499,0.002855642,0.0009747666,0.0001805993,0.001252205,0.0005348929,0.01100685,0.6917994,0.001361109,0.005025608,0.2833345],"study_design_scores_gemma":[0.0001102593,0.000733695,0.03043001,0.000116672,0.0002383983,0.003182266,0.0004587289,0.04452578,0.8981442,0.001384048,0.02053907,0.0001367597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6540743,0.002398528,0.3214073,0.0005302866,0.0005800683,0.0002884755,0.0006554463,0.006883153,0.01318263],"genre_scores_gemma":[0.785188,0.001759193,0.1965943,0.0003912674,0.0001001068,0.0001001862,0.001189431,0.001238162,0.01343929],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006709101,"threshold_uncertainty_score":0.02244419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0171727493652327,"score_gpt":0.2439858995792696,"score_spread":0.2268131502140369,"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."}}