{"id":"W4396832716","doi":"10.1145/3613904.3641927","title":"TimeTunnel: Integrating Spatial and Temporal Motion Editing for Character Animation in Virtual Reality","year":2024,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Autodesk (Canada)","funders":"","keywords":"Animation; Computer science; Character animation; Computer animation; Motion (physics); Character (mathematics); Motion capture; Skeletal animation; Virtual reality; Interface (matter); Computer facial animation; Computer graphics (images); Representation (politics); Set (abstract data type); Artificial intelligence; Computer vision; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002609784,0.00007050207,0.00007149805,0.0001007794,0.00002819089,0.0001167678,0.00001753302,0.00004633813,0.00007741312],"category_scores_gemma":[0.00003576756,0.00006614884,0.0000200492,0.00006594712,0.0000067422,0.0003217073,0.000005886821,0.00008499828,0.00001332242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004631293,"about_ca_system_score_gemma":0.000003679239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000402569,"about_ca_topic_score_gemma":0.0001698098,"domain_scores_codex":[0.9995453,0.0000134887,0.0001893118,0.0001079424,0.000055311,0.00008864329],"domain_scores_gemma":[0.9998852,0.0000328657,0.00001242581,0.00003286227,0.00001564448,0.0000210059],"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":[0.00002289422,0.00005841018,0.004469643,0.001272348,0.00004415263,0.000005816562,0.006556291,0.003250549,0.0697046,0.08943342,0.004931367,0.8202505],"study_design_scores_gemma":[0.0001211512,0.00002531548,0.006704886,0.00008144859,0.000003131402,0.000001460249,0.0001614579,0.9905979,0.0007808012,0.000397402,0.001051824,0.00007322486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3112178,0.00001687786,0.6856722,0.0001837581,0.0003646102,0.0001824557,0.00001097857,0.0003800882,0.001971169],"genre_scores_gemma":[0.9984891,0.000002613082,0.0008472081,0.00001614885,0.0003868694,0.00001783379,0.0001047629,0.00001440435,0.0001210057],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9873474,"threshold_uncertainty_score":0.2697471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02056073165007212,"score_gpt":0.2574322315420838,"score_spread":0.2368714998920117,"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."}}