{"id":"W4387929395","doi":"10.1145/3618327","title":"Interaction-Driven Active 3D Reconstruction with Object Interiors","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Artificial intelligence; Computer vision; Computer science; Object (grammar); Active perception; Robot; Focus (optics); Feature (linguistics); 3D reconstruction; Active vision; Computer graphics (images); Optics","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":[0.0007405885,0.0007397844,0.000793838,0.0007211232,0.0003012582,0.001343405,0.001655174,0.001049173,0.002220222],"category_scores_gemma":[0.001659019,0.0007760826,0.001050149,0.0004865176,0.00101493,0.001240989,0.001661554,0.001118847,0.0007858808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004632419,"about_ca_system_score_gemma":0.0006221413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001322515,"about_ca_topic_score_gemma":0.001854952,"domain_scores_codex":[0.9994231,0.00008803154,0.00002126515,0.00009659747,0.0003352643,0.00003582416],"domain_scores_gemma":[0.9993468,0.0002549187,0.00007119641,0.0001757592,0.0001235267,0.00002769882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002296714,0.0001158595,0.001027439,0.0002573688,0.00009311285,0.0002513191,0.0004841421,0.5601756,0.1406416,0.02154307,0.001800162,0.2733807],"study_design_scores_gemma":[0.000007923975,0.00002804114,0.0001392435,0.00001010829,0.000008092554,0.0001340415,0.00002103606,0.9708256,0.02406845,0.002558246,0.00218234,0.00001680378],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003022964,0.00002837967,0.9961694,0.00002126579,0.000005167079,0.0000124255,0.00001502885,0.0003211983,0.0004041585],"genre_scores_gemma":[0.1396852,0.0001069009,0.8575292,0.00006280737,0.00001560863,0.00007799176,0.0001739295,0.0003560698,0.001992363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002220222,"threshold_uncertainty_score":0.007427335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445550272999827,"score_gpt":0.2257019446694668,"score_spread":0.2112464419394685,"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."}}