{"id":"W4293863180","doi":"10.1109/siu55565.2022.9864922","title":"A Survey of 3D Object Reconstruction Methods","year":2022,"lang":"en","type":"article","venue":"2022 30th Signal Processing and Communications Applications Conference (SIU)","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Polygon mesh; Point cloud; Computer science; Artificial intelligence; Voxel; Deep learning; Benchmark (surveying); Iterative reconstruction; Object (grammar); 3D reconstruction; Computer vision; Artificial neural network; Deep neural networks; Pattern recognition (psychology); Point (geometry); 3d model; Computer graphics (images); Mathematics; Cartography","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00168613,0.0001410685,0.0002293574,0.0001103674,0.001629727,0.00009647063,0.0007649455,0.00004689937,0.001220019],"category_scores_gemma":[0.00002727704,0.0001362843,0.00003449927,0.000951829,0.0003476116,0.000190551,0.0001422285,0.0003887413,0.000009784683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001179187,"about_ca_system_score_gemma":0.0002517624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002556171,"about_ca_topic_score_gemma":0.001474562,"domain_scores_codex":[0.9978598,0.001034111,0.0003962379,0.0003045673,0.00021398,0.0001912396],"domain_scores_gemma":[0.9983187,0.0004310638,0.0002806339,0.0006344207,0.0002524554,0.0000827586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001416775,0.00004430212,0.04359705,0.00002541608,0.00001356402,9.068758e-8,0.0003551897,0.000193895,0.0003396255,0.0002322029,0.00003277903,0.9551517],"study_design_scores_gemma":[0.0006872808,0.0003721448,0.5243641,0.00008771371,0.0001226996,0.0001356241,0.008132291,0.4269681,0.0002826625,0.006077506,0.03178057,0.0009894004],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4648805,0.1139511,0.2734892,0.00303386,0.0004330073,0.004528299,0.004789823,0.001127483,0.1337667],"genre_scores_gemma":[0.9734606,0.0004710071,0.02495091,0.00005442919,0.00001101589,0.0001354613,0.0006645411,0.000005564097,0.0002464356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9541623,"threshold_uncertainty_score":0.999693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07693416553029708,"score_gpt":0.3150692709283358,"score_spread":0.2381351053980387,"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."}}