{"id":"W4402727731","doi":"10.1109/cvpr52733.2024.01985","title":"PAPR in Motion: Seamless Point-level 3D Scene Interpolation","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Interpolation (computer graphics); Computer science; Computer vision; Motion (physics); Computer graphics (images); Point (geometry); Artificial intelligence; Mathematics; Geometry","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":[0.0006375271,0.0009829529,0.0007659683,0.0005163569,0.0003460926,0.000944417,0.001474753,0.0009513766,0.002784458],"category_scores_gemma":[0.001595363,0.0005918355,0.001160295,0.0005234832,0.0007920397,0.001125345,0.002348756,0.002158732,0.0008355766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004746002,"about_ca_system_score_gemma":0.0006335329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001810291,"about_ca_topic_score_gemma":0.003046961,"domain_scores_codex":[0.9994568,0.00008876458,0.00001556752,0.0001165583,0.00026879,0.00005344789],"domain_scores_gemma":[0.9996501,0.00009891255,0.00003390644,0.0001379606,0.00004338057,0.00003562615],"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":[0.000499161,0.0002141074,0.001340747,0.0004137594,0.0001592253,0.0004468693,0.0005703324,0.4526195,0.1137727,0.05036397,0.01071039,0.3688892],"study_design_scores_gemma":[0.00003966528,0.00009338038,0.00023521,0.00001908665,0.00001611863,0.0002450385,0.00004190072,0.9639581,0.01530273,0.01243017,0.007589426,0.00002928706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007625372,0.0001064791,0.9890342,0.0001088755,0.00003985584,0.00003746986,0.00008294189,0.001628495,0.001336312],"genre_scores_gemma":[0.2223779,0.0002803064,0.7731605,0.0001899564,0.00006602175,0.00008690936,0.000427458,0.0006675494,0.002743412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002784458,"threshold_uncertainty_score":0.009314954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02930357247357336,"score_gpt":0.3050992219203529,"score_spread":0.2757956494467796,"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."}}