{"id":"W4361188948","doi":"10.48550/arxiv.2303.13805","title":"Seeing Through the Glass: Neural 3D Reconstruction of Object Inside a Transparent Container","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canada Excellence Research Chairs, Government of Canada; Commonwealth Scientific and Industrial Research Organisation","keywords":"Rendering (computer graphics); Computer science; Artificial intelligence; Computer vision; Computer graphics (images); Global illumination; Object (grammar); Subspace topology; Ray tracing (physics); Visualization; Optics; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003698603,0.0008064967,0.0005310923,0.0004775717,0.0002104107,0.0009727023,0.00110271,0.001103349,0.001178276],"category_scores_gemma":[0.0008875082,0.0005338503,0.001058878,0.0004797443,0.0006575327,0.0009171505,0.0009841227,0.00136685,0.0004654162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005125324,"about_ca_system_score_gemma":0.0007453152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007671317,"about_ca_topic_score_gemma":0.007472365,"domain_scores_codex":[0.999831,0.000025691,0.000005713423,0.00004364648,0.00007087935,0.00002300931],"domain_scores_gemma":[0.9998272,0.0000553372,0.00002602951,0.00004492957,0.00002767991,0.00001887341],"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":[0.0002179183,0.00007618194,0.001161345,0.0001344175,0.0001030923,0.000376561,0.0002007876,0.7279344,0.04647554,0.01075294,0.004122965,0.2084438],"study_design_scores_gemma":[0.000004590566,0.0000105955,0.0001050499,0.00000498643,0.000005108581,0.00005942132,0.00001322381,0.9943328,0.003176905,0.0018051,0.0004750985,0.000007251665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02699989,0.0001636947,0.9700757,0.0001936296,0.00003322794,0.00002221579,0.0001063256,0.001264979,0.001140386],"genre_scores_gemma":[0.3887443,0.0005164245,0.6036173,0.0002705798,0.00006457648,0.00006216909,0.0008199232,0.0005212924,0.005383407],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007671317,"threshold_uncertainty_score":0.01525337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1243500920512244,"score_gpt":0.2331901969219489,"score_spread":0.1088401048707245,"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."}}