{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002486809,0.0007896071,0.0004029596,0.0001996176,0.0002247973,0.0004734654,0.001046105,0.0005857931,0.003397515],"category_scores_gemma":[0.001541574,0.0004075759,0.0003509623,0.0001120027,0.0003462482,0.0005452919,0.000862231,0.0008786254,0.0007333807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004644872,"about_ca_system_score_gemma":0.000635983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0106082,"about_ca_topic_score_gemma":0.01530774,"domain_scores_codex":[0.9998664,0.00001548725,0.000005732301,0.00005847818,0.000032406,0.00002145682],"domain_scores_gemma":[0.9997529,0.0001068427,0.00001926878,0.0000394265,0.00003906427,0.00004243919],"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":[0.0004266122,0.0003859792,0.004774516,0.000275073,0.0001506304,0.0004924161,0.0003660726,0.7111697,0.06138106,0.00317409,0.007209459,0.2101944],"study_design_scores_gemma":[0.00002234628,0.00005204698,0.0005688744,0.000008035186,0.000009559561,0.00003166644,0.00002709246,0.9920698,0.005022997,0.0009314016,0.001248524,0.000007709497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2344967,0.0002570267,0.7338618,0.0002920638,0.0001387494,0.0002864435,0.001008017,0.02047845,0.009180737],"genre_scores_gemma":[0.8664412,0.0001346873,0.125546,0.0001231745,0.00002165283,0.0002472775,0.001843795,0.0003603293,0.005281855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0106082,"threshold_uncertainty_score":0.02109289,"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."}}