{"id":"W4200521614","doi":"10.1145/3478513.3480483","title":"Continuous aerial path planning for 3D urban scene reconstruction","year":2021,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Motion planning; Computer vision; Trajectory; Drone; Artificial intelligence; Path (computing); Aerial image; Benchmark (surveying); 3D reconstruction; Tree (set theory); Image (mathematics); Mathematics; Robot; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.00006624003,0.000136749,0.0001570338,0.0001278088,0.0001833173,0.00005061405,0.00007318761,0.0001435564,0.00003396416],"category_scores_gemma":[0.0000305464,0.0001588686,0.0001102145,0.0003002712,0.00002969942,0.0000864358,0.000001078175,0.0001730854,0.000003478951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003235361,"about_ca_system_score_gemma":0.00002663883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004251596,"about_ca_topic_score_gemma":0.00001167072,"domain_scores_codex":[0.9992738,0.00002114757,0.0002166918,0.0001834664,0.0001090555,0.000195861],"domain_scores_gemma":[0.9994165,0.00009850497,0.00002582332,0.0002849727,0.0001119168,0.00006226478],"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":[0.00009719247,0.0001396148,0.0005168689,0.0001615423,0.0002372834,0.00002013111,0.0005033835,0.8795891,0.008210814,0.001742154,0.001239157,0.1075427],"study_design_scores_gemma":[0.003325426,0.0003428597,0.0007301005,0.0003341795,0.0003170579,0.0001239486,0.0004198575,0.9069399,0.0516262,0.005590033,0.02921832,0.001032162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03159535,0.0001600588,0.9658015,0.0001098319,0.001697753,0.0001578621,0.00005991399,0.0002453701,0.0001723282],"genre_scores_gemma":[0.9607562,0.000223629,0.038454,0.0001252955,0.0001945289,0.0000373648,0.00008775329,0.00005580115,0.00006540825],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9291609,"threshold_uncertainty_score":0.6478475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01766700097408987,"score_gpt":0.2259841479968258,"score_spread":0.2083171470227359,"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."}}