{"id":"W4413145014","doi":"10.1109/cvpr52734.2025.01032","title":"FruitNinja: 3D Object Interior Texture Generation with Gaussian Splatting","year":2025,"lang":"en","type":"article","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Texture (cosmology); Artificial intelligence; Computer vision; Computer graphics (images); Gaussian; Object (grammar); Image (mathematics); Physics","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":[0.0004648246,0.0009897527,0.0005858578,0.0007256026,0.0002650134,0.001170716,0.001578103,0.0006962058,0.006366716],"category_scores_gemma":[0.001192699,0.0005629119,0.00113375,0.0004573262,0.0005068547,0.0007045436,0.001477573,0.001259827,0.002164751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004884206,"about_ca_system_score_gemma":0.0005646126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002501155,"about_ca_topic_score_gemma":0.0044061,"domain_scores_codex":[0.999725,0.00002132965,0.00001042295,0.00005916043,0.0001562213,0.00002778599],"domain_scores_gemma":[0.9996632,0.00009833842,0.00002337186,0.0001285336,0.00005209482,0.00003445695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004613682,0.0002088696,0.002202187,0.0005861749,0.0001809065,0.0006309581,0.0006071104,0.1667025,0.1322919,0.01343011,0.04197716,0.6407208],"study_design_scores_gemma":[0.00009241483,0.0000936945,0.0007576625,0.00003137469,0.00002912041,0.0004867083,0.00004687109,0.9223717,0.04554499,0.006479864,0.02401365,0.00005196847],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01638286,0.0004034495,0.9501894,0.0001288692,0.0001018296,0.0001305042,0.0006463684,0.027242,0.004774763],"genre_scores_gemma":[0.2157951,0.0004925375,0.7652307,0.0002746018,0.00004468009,0.0002207862,0.003430234,0.007107975,0.007403442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006366716,"threshold_uncertainty_score":0.02129883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01385150009443461,"score_gpt":0.2831319926791733,"score_spread":0.2692804925847387,"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."}}