{"id":"W4414903942","doi":"10.1109/iccv51701.2025.00685","title":"Dynamic Point Maps: A Versatile Representation for Dynamic 3D Reconstruction","year":2025,"lang":"en","type":"preprint","venue":"","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geomechanica (Canada)","funders":"","keywords":"Intrinsics; Point cloud; Point (geometry); Optical flow; Object (grammar); Representation (politics); Bundle adjustment; Intuition","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001173573,0.0002438995,0.0003477544,0.0003321819,0.00005834855,0.00007302236,0.0001591893,0.0002723059,0.00009954004],"category_scores_gemma":[0.0000394518,0.0002654748,0.0002871004,0.0001479399,0.00001620667,0.00007096575,0.00009019791,0.000296409,0.00001763148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003117703,"about_ca_system_score_gemma":0.00004940488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001239305,"about_ca_topic_score_gemma":0.0002470266,"domain_scores_codex":[0.9988359,0.00002000748,0.0003992956,0.0004274916,0.000115121,0.0002021936],"domain_scores_gemma":[0.9992787,0.00006318845,0.00006778356,0.0004541776,0.00009529554,0.00004086704],"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":[0.000008403294,0.000008171249,0.00002162127,0.0004459054,0.0002846799,5.404897e-7,0.0001417933,0.9398271,0.0001413744,0.0000350542,0.0009472209,0.0581381],"study_design_scores_gemma":[0.0002086395,0.000006611202,0.0000167616,0.0001977663,0.0002060137,0.0000022382,0.0002047067,0.9930775,0.0001206099,0.005600213,0.0001086356,0.0002502967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01421004,0.0002886853,0.9722442,0.0002106175,0.001532861,0.0004644334,0.0002855377,0.0008329094,0.009930742],"genre_scores_gemma":[0.9046177,0.0005227954,0.08700923,0.00003528639,0.00006086802,0.0002981497,0.001485657,0.00005253552,0.005917793],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8904077,"threshold_uncertainty_score":0.9999797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01152660141024609,"score_gpt":0.2620115549607596,"score_spread":0.2504849535505135,"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."}}