{"id":"W3202239164","doi":"10.1109/iccv48922.2021.00351","title":"Towards Rotation Invariance in Object Detection","year":2021,"lang":"en","type":"article","venue":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Rotation (mathematics); Ellipse; Minimum bounding box; Code (set theory); Computer science; Differentiable function; Bounding overwatch; Object detection; Artificial intelligence; Object (grammar); Bin; Ambiguity; Algorithm; Computer vision; Mathematics; Pattern recognition (psychology); Geometry; Image (mathematics); Mathematical analysis","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":[0.0004601157,0.0003017584,0.0002955082,0.0005460255,0.0001418282,0.0007956061,0.000985686,0.000173056,0.0004147787],"category_scores_gemma":[0.0000848391,0.0003159752,0.0001529349,0.0008643401,0.00003636088,0.001165973,0.0003254883,0.0004869092,0.0002897341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000400403,"about_ca_system_score_gemma":0.0002966695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001524599,"about_ca_topic_score_gemma":0.0002417983,"domain_scores_codex":[0.9970621,0.000277853,0.0005817459,0.0009441462,0.0007987671,0.0003354153],"domain_scores_gemma":[0.9981036,0.0001051503,0.0002122695,0.0006296189,0.0008430299,0.0001063289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006502605,0.0003069729,0.00005406118,0.00001678169,0.00003848683,0.0003462091,0.0004258284,0.0004563054,0.03687956,0.01911971,0.001463745,0.9408273],"study_design_scores_gemma":[0.0008681311,0.0004662542,0.003897826,0.0002947625,0.00000491988,0.0001379718,0.00005120387,0.4548996,0.5226151,0.01243095,0.003815883,0.0005173474],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01124422,0.00002763077,0.9704687,0.002818225,0.003877805,0.0002336267,0.00000677924,0.0002686426,0.01105436],"genre_scores_gemma":[0.9564804,0.0001501303,0.04049211,0.001455818,0.0004820353,0.00006779515,0.0000235381,0.00002017618,0.0008280153],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9452361,"threshold_uncertainty_score":0.9999292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02575516182990505,"score_gpt":0.3001403775619439,"score_spread":0.2743852157320389,"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."}}