{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000595459,0.00007755093,0.00006558335,0.00008315434,0.00005927639,0.0003006167,0.0002224437,0.00004386036,0.0008696779],"category_scores_gemma":[0.000003818666,0.00006182814,0.00005398289,0.000173681,0.000009021956,0.0008509647,0.00007736363,0.0000811377,0.0008172194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001753097,"about_ca_system_score_gemma":0.00002414641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005345317,"about_ca_topic_score_gemma":0.00000841488,"domain_scores_codex":[0.9992969,0.0000228169,0.0001156108,0.0002882847,0.00015872,0.000117638],"domain_scores_gemma":[0.9996463,0.00005188601,0.000008933895,0.0002102065,0.00002422094,0.00005847211],"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":[0.000008836628,0.000168801,0.00002650152,0.00004350938,0.00007108471,0.00009192136,0.003910385,0.0001201038,0.03390539,0.2449761,0.02134929,0.6953281],"study_design_scores_gemma":[0.000130004,0.0000186743,0.0001747456,0.00003879212,0.000003897318,0.000002713887,0.00001648692,0.8535342,0.004003097,0.1394219,0.002552605,0.0001029721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1018196,0.00009761118,0.8566278,0.0008264665,0.0005265026,0.00008258332,0.000005615987,0.0007639502,0.0392499],"genre_scores_gemma":[0.9855452,0.0000268675,0.0109271,0.0005519008,0.0001212904,0.000008098881,0.00001671612,0.000007028606,0.002795831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8837256,"threshold_uncertainty_score":0.9999608,"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."}}