{"id":"W4384263613","doi":"10.48550/arxiv.2307.05832","title":"Bag of Views: An Appearance-based Approach to Next-Best-View Planning for 3D Reconstruction","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Toolbox; Computer science; Task (project management); Artificial intelligence; Machine learning; 3D reconstruction; Reinforcement learning; Computer vision; Engineering","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":[0.0001977621,0.0002689095,0.0004152948,0.0003455117,0.00007147741,0.00003978039,0.0002945919,0.0002740828,0.000005380674],"category_scores_gemma":[0.00002406427,0.0003381884,0.0001563634,0.0004523279,0.00004083987,0.0001279654,0.0000638273,0.0002359952,0.00001667278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001374926,"about_ca_system_score_gemma":0.00005842723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004162909,"about_ca_topic_score_gemma":0.0000123522,"domain_scores_codex":[0.998787,0.00005383515,0.0002846872,0.0005502576,0.00006626868,0.0002579629],"domain_scores_gemma":[0.9990677,0.0000426449,0.0001171093,0.0005100482,0.0001305459,0.0001319523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003937682,0.00003975966,0.0002937248,0.001124388,0.00005396955,0.000004666136,0.00009770574,0.9944634,0.000141212,0.001544873,0.00005737086,0.002139582],"study_design_scores_gemma":[0.0003703379,0.0000643616,0.00009740481,0.0006217724,0.0001026894,9.410841e-7,0.0001664878,0.9968789,0.0002378514,0.0006821138,0.0004335016,0.0003436917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09413887,0.0001259491,0.9034155,0.000007204808,0.0005643853,0.0006728568,0.00004234444,0.0002748644,0.0007580376],"genre_scores_gemma":[0.9816403,0.0001414597,0.01767485,0.00002457583,0.000109323,0.000007303959,0.0001802472,0.00008127129,0.0001406378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8875015,"threshold_uncertainty_score":0.999907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2078174841096492,"score_gpt":0.2182455215800714,"score_spread":0.01042803747042217,"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."}}