{"id":"W4285163934","doi":"10.1109/tmm.2022.3187856","title":"C$^{2}$DFNet: Criss-Cross Dynamic Filter Network for RGB-D Salient Object Detection","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Science Foundation of Liaoning Province; National Natural Science Foundation of China","keywords":"Computer science; Artificial intelligence; RGB color model; Computer vision; Context (archaeology); Convolution (computer science); Modality (human–computer interaction); Filter (signal processing); Salient; Pattern recognition (psychology); Artificial neural network","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":[0.0003637664,0.00106289,0.0005204667,0.0008582274,0.00041984,0.0006059423,0.001660325,0.0008788108,0.008826355],"category_scores_gemma":[0.000962648,0.0003758319,0.0005899674,0.0006815337,0.0003804124,0.0009612284,0.0009815033,0.0008352686,0.002213082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001099073,"about_ca_system_score_gemma":0.001090082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0257208,"about_ca_topic_score_gemma":0.03382782,"domain_scores_codex":[0.9998139,0.00001523922,0.000006827634,0.00008164289,0.00004262549,0.00003987652],"domain_scores_gemma":[0.9998701,0.00002769818,0.00001241613,0.00002626914,0.00005000625,0.00001349905],"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":[0.0004873487,0.0002540637,0.00169868,0.000180273,0.0001309853,0.0002520306,0.00007418135,0.1330917,0.03652197,0.01491591,0.05269851,0.7596943],"study_design_scores_gemma":[0.00001834609,0.00004477831,0.0006844493,0.00001467953,0.00001937133,0.00008490715,0.00001221068,0.9748535,0.009530448,0.006616676,0.00810308,0.00001766258],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03119308,0.000666344,0.9443566,0.0004626932,0.0002677337,0.0001584345,0.002026065,0.01207942,0.008789606],"genre_scores_gemma":[0.5236976,0.0008903646,0.439715,0.0009203952,0.0001920991,0.0004637528,0.008132862,0.0009427148,0.02504528],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0257208,"threshold_uncertainty_score":0.05114222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01810113609284413,"score_gpt":0.2926798188489161,"score_spread":0.2745786827560719,"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."}}