{"id":"W4392251861","doi":"10.1109/tetci.2024.3358103","title":"Skeletal Video Anomaly Detection Using Deep Learning: Survey, Challenges, and Future Directions","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Emerging Topics in Computational Intelligence","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; AGE-WELL; Alzheimer's Association","keywords":"Anomaly detection; Deep learning; Computer science; Anomaly (physics); Artificial intelligence; Physics","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":[0.003955206,0.001214566,0.001484443,0.002250344,0.0004910846,0.002196474,0.003431831,0.001926132,0.001362279],"category_scores_gemma":[0.008100252,0.0005339452,0.0008535287,0.002449236,0.001472567,0.0045774,0.001675057,0.002668218,0.0006638356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001522104,"about_ca_system_score_gemma":0.0015328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005600721,"about_ca_topic_score_gemma":0.004192904,"domain_scores_codex":[0.9978035,0.0005304208,0.0001647495,0.0004647643,0.0009039557,0.0001325195],"domain_scores_gemma":[0.9941993,0.00314862,0.0003590629,0.0006503632,0.00142216,0.0002203795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008675808,0.0002146202,0.005368484,0.0006423994,0.0001250201,0.00007993383,0.0001094263,0.02639279,0.001818415,0.01873314,0.01313328,0.9332958],"study_design_scores_gemma":[0.00002532052,0.0002440478,0.002952005,0.0005795106,0.0001001748,0.0006205284,0.0003175714,0.8711126,0.008513662,0.06765147,0.04779731,0.00008578917],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.02901813,0.1549083,0.7892261,0.01565826,0.0006335385,0.0002543161,0.0004238344,0.002270302,0.00760723],"genre_scores_gemma":[0.4568011,0.1604197,0.3658464,0.003534614,0.001960508,0.0003095526,0.001734142,0.0003243131,0.009069696],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005600721,"threshold_uncertainty_score":0.02091736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04009611501808458,"score_gpt":0.3082281182185302,"score_spread":0.2681320032004456,"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."}}