{"id":"W3173438721","doi":"10.1109/tpami.2021.3090917","title":"View-Aware Geometry-Structure Joint Learning for Single-View 3D Shape Reconstruction","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Artificial intelligence; 3D reconstruction; Iterative reconstruction; Computer vision; Computer science; Feature (linguistics); Geometry; Active shape model; Focus (optics); Embedding; Shape analysis (program analysis); Solid modeling; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005516956,0.001275656,0.0008917468,0.0008091589,0.0002038415,0.0008503611,0.001581153,0.001142409,0.002678359],"category_scores_gemma":[0.001572429,0.0007316801,0.00130141,0.001008212,0.0008701577,0.001643956,0.001650349,0.001782402,0.001474152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006700593,"about_ca_system_score_gemma":0.00106634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003942457,"about_ca_topic_score_gemma":0.008149659,"domain_scores_codex":[0.9996517,0.00004589789,0.0000148312,0.00009915978,0.000154264,0.0000341665],"domain_scores_gemma":[0.9996364,0.0000924009,0.00003743913,0.0001350355,0.00007171423,0.00002697331],"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":[0.0001532334,0.00008374434,0.001121152,0.0001910451,0.0001387844,0.000184614,0.00009947097,0.5469379,0.03036532,0.01176711,0.006595609,0.4023621],"study_design_scores_gemma":[0.000005537645,0.00002427824,0.0001266308,0.00000834099,0.00000952492,0.0001009373,0.00001114849,0.9883032,0.005213042,0.005093803,0.001095264,0.000008306832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008875317,0.0002538954,0.9878464,0.0001020534,0.00002732924,0.00002363142,0.0001521819,0.001595492,0.001123667],"genre_scores_gemma":[0.365816,0.0009177958,0.623062,0.0004795478,0.00005720106,0.0001188221,0.002791912,0.0006545697,0.006102057],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003942457,"threshold_uncertainty_score":0.008960009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387951554921526,"score_gpt":0.2423705836567177,"score_spread":0.2184910681075024,"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."}}