{"id":"W4389539423","doi":"10.1145/3610548.3618149","title":"iNVS: Repurposing Diffusion Inpainters for Novel View Synthesis","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Epipolar geometry; Inpainting; Pixel; Masking (illustration); View synthesis; Prior probability; Image (mathematics)","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":[0.0006975792,0.001076004,0.0008347788,0.0007115754,0.0002241937,0.0007275347,0.001429062,0.0008293276,0.003866556],"category_scores_gemma":[0.001429987,0.0005107647,0.0009469404,0.0003584845,0.0005471642,0.0008574573,0.00123587,0.00149784,0.001326469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003899834,"about_ca_system_score_gemma":0.000461079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052541,"about_ca_topic_score_gemma":0.002736778,"domain_scores_codex":[0.9995887,0.00005178295,0.00001549826,0.0001080586,0.0001961952,0.00003981651],"domain_scores_gemma":[0.9995531,0.0001596973,0.00005064396,0.0001329995,0.00006902498,0.00003455871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003237636,0.0001839253,0.0008810608,0.0004170788,0.0001732233,0.0002209123,0.0002478322,0.1665888,0.1521432,0.01353611,0.01393713,0.6513469],"study_design_scores_gemma":[0.00006409553,0.0001529236,0.0003856932,0.00002330574,0.00002752055,0.0003713754,0.00003359376,0.9312409,0.04927399,0.006720176,0.01168237,0.00002413284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006837748,0.0002811833,0.989262,0.00006465619,0.00004870847,0.00004490172,0.0001534064,0.002355362,0.0009520332],"genre_scores_gemma":[0.1574948,0.000474816,0.8353155,0.0001948492,0.000112749,0.0001052935,0.001088865,0.0008569431,0.004356293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003866556,"threshold_uncertainty_score":0.01293492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03973268932945306,"score_gpt":0.3084888956744522,"score_spread":0.2687562063449991,"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."}}