{"id":"W3107529234","doi":"10.1109/cvpr46437.2021.01393","title":"DeRF: Decomposed Radiance Fields","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Simon Fraser University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Radiance; Rendering (computer graphics); Computer science; Inference; Limiting; Deep neural networks; Artificial neural network; Voronoi diagram; Artificial intelligence; Decomposition; Computer vision; Global illumination; Algorithm; Computer graphics (images); Remote sensing; Mathematics; Geography; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004918149,0.0009211685,0.0005582835,0.0007667574,0.000228499,0.001009248,0.001300534,0.00106836,0.01129449],"category_scores_gemma":[0.001882114,0.0004568127,0.0008228936,0.0004591402,0.000377167,0.00138215,0.0009622432,0.001478989,0.002791658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005086947,"about_ca_system_score_gemma":0.000594453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003371966,"about_ca_topic_score_gemma":0.004607838,"domain_scores_codex":[0.9997521,0.0000467306,0.000008559192,0.00005338192,0.0001119774,0.00002720414],"domain_scores_gemma":[0.9996834,0.0001105439,0.0000231478,0.00008351248,0.00007432246,0.00002515026],"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":[0.0002951649,0.0001221125,0.0007323279,0.0003109456,0.00009264871,0.0002589568,0.0001411612,0.3912595,0.04424207,0.05162447,0.02853696,0.4823838],"study_design_scores_gemma":[0.00003049303,0.00001916415,0.0001912551,0.00001879682,0.00000886787,0.0001526287,0.00001500209,0.9607407,0.009153298,0.01576457,0.01388477,0.0000203201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003220664,0.0001278314,0.9912141,0.0001397933,0.00005604788,0.00002636257,0.0003597319,0.002588904,0.002266562],"genre_scores_gemma":[0.1283181,0.0003918865,0.8581302,0.0003642383,0.00008061648,0.0001065181,0.001980163,0.001441791,0.00918653],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01129449,"threshold_uncertainty_score":0.0377838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02044352253078601,"score_gpt":0.2969076180212772,"score_spread":0.2764640954904912,"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."}}