{"id":"W4402753820","doi":"10.1109/cvpr52733.2024.02153","title":"Unsupervised Keypoints from Pretrained Diffusion Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Human Pose and Action Recognition","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Google","keywords":"Computer science; Diffusion; Artificial intelligence; Pattern recognition (psychology); 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":[0.0009028888,0.002029385,0.001602196,0.0018766,0.0005054587,0.001559559,0.002664431,0.002316368,0.005038962],"category_scores_gemma":[0.00480057,0.0008631842,0.001588664,0.001399366,0.001016391,0.00339839,0.002175278,0.003194816,0.003594031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001209639,"about_ca_system_score_gemma":0.001066161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007565532,"about_ca_topic_score_gemma":0.01149109,"domain_scores_codex":[0.9994549,0.00007450586,0.00002541901,0.0002752153,0.00009850665,0.0000714648],"domain_scores_gemma":[0.9986637,0.0004824261,0.000184342,0.000332561,0.0002546353,0.00008238389],"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":[0.0003899507,0.000120703,0.001966127,0.0002879251,0.0001923972,0.0002015518,0.0002070969,0.6340355,0.0176074,0.02304153,0.01525257,0.3066973],"study_design_scores_gemma":[0.00002527341,0.00003014907,0.0002086503,0.00001746106,0.000012827,0.00004933216,0.00001880515,0.9768002,0.003133662,0.01836918,0.001321663,0.00001286646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02825351,0.0007295095,0.9616427,0.0003251977,0.0001295817,0.0001004298,0.0007750458,0.006532967,0.001511097],"genre_scores_gemma":[0.5822442,0.00106588,0.3917294,0.0004346132,0.0002903701,0.0002843066,0.006689667,0.001962625,0.01529897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007565532,"threshold_uncertainty_score":0.01685703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02545054772849654,"score_gpt":0.234685649183588,"score_spread":0.2092351014550914,"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."}}