{"id":"W6979333517","doi":"","title":"Fr\\'echet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos","year":2024,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Image and Video Quality Assessment","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Vector Institute; Natural Sciences and Engineering Research Council of Canada; Government of Canada; Canadian Institute for Advanced Research","keywords":"Video tracking; Metric (unit); Video quality; Motion (physics); Consistency (knowledge bases); Motion compensation; Noise (video); Motion estimation; Block-matching algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00111966,0.0001593479,0.0001889053,0.0004882888,0.0001446955,0.0002002928,0.000464603,0.0000852296,0.00001666685],"category_scores_gemma":[0.0001975037,0.0001774356,0.0001417059,0.002105918,0.00004312199,0.001324339,0.0001458467,0.0001741987,0.00004727759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003988183,"about_ca_system_score_gemma":0.0001334012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001081259,"about_ca_topic_score_gemma":0.00006650574,"domain_scores_codex":[0.9983519,0.0001996017,0.0002573761,0.0007364706,0.0001369897,0.000317629],"domain_scores_gemma":[0.9988362,0.000410978,0.0000845903,0.0004487982,0.000144129,0.00007532761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003809922,0.0002141862,0.002068658,0.0003468442,0.00006132772,0.0002105899,0.001034798,0.01831552,0.0008685149,0.9238967,0.0005197944,0.05242503],"study_design_scores_gemma":[0.0005939899,0.0001174466,0.001614118,0.0001099372,0.00003902451,0.000003852711,0.0002157424,0.9445075,0.0005893918,0.05133272,0.0006492831,0.0002270092],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04969274,0.0002160999,0.9479209,0.000382688,0.0003737208,0.0003957399,0.000008122645,0.0001997163,0.0008102425],"genre_scores_gemma":[0.9931777,0.00003001431,0.006065053,0.0001110184,0.00004043004,0.000005385898,0.000009384981,0.00001074536,0.0005503381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9434849,"threshold_uncertainty_score":0.7235614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1352585333986323,"score_gpt":0.27817017105867,"score_spread":0.1429116376600377,"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."}}