{"id":"W4385271020","doi":"10.1145/3592408","title":"Learning Physically Simulated Tennis Skills from Broadcast Videos","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Human Motion and Animation","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Toronto","funders":"","keywords":"Racket; Computer science; Tennis ball; Imitation; Embedding; Motion (physics); Ball (mathematics); Motion capture; Broadcasting (networking); Scale (ratio); Rendezvous; Artificial intelligence; Multimedia","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006127331,0.0001427328,0.0001251475,0.0002557733,0.0002075707,0.00004912995,0.0001418124,0.0001018959,0.0002541737],"category_scores_gemma":[0.00002476429,0.0001545013,0.0001189986,0.0007597078,0.0000282572,0.0001399574,0.000002418414,0.0004128003,0.000820629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002208564,"about_ca_system_score_gemma":0.000005865174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001591427,"about_ca_topic_score_gemma":0.00001307174,"domain_scores_codex":[0.9992473,0.0000302641,0.0001756548,0.0001707414,0.0001796686,0.0001963324],"domain_scores_gemma":[0.9994438,0.0001710351,0.00001922236,0.0002555741,0.00003796504,0.00007237993],"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":[0.000008211693,0.0001119561,0.0001720451,0.00002668302,0.0001391464,0.000008422408,0.001358961,0.8678664,0.01869311,0.0001515461,0.0004222452,0.1110413],"study_design_scores_gemma":[0.001494875,0.0002353673,0.03415197,0.0001903335,0.0001262362,0.00000241771,0.0004666173,0.9159728,0.0100059,0.007251726,0.02923526,0.0008665314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.883342,0.00001878979,0.1124222,0.0003041707,0.000352343,0.0001542992,0.00005052429,0.002942158,0.0004135181],"genre_scores_gemma":[0.9989179,0.0002289353,0.0002789437,0.00009528082,0.00005388637,0.000009104819,0.00007767296,0.00004601487,0.0002923096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1155758,"threshold_uncertainty_score":0.9999573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01198648284984992,"score_gpt":0.2300836364431626,"score_spread":0.2180971535933127,"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."}}