{"id":"https://openalex.org/W4221079664","doi":"https://doi.org/10.1109/tip.2022.3162099","title":"CrabNet: Fully Task-Specific Feature Learning for One-Stage Object Detection","display_name":"CrabNet: Fully Task-Specific Feature Learning for One-Stage Object Detection","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4221079664","doi":"https://doi.org/10.1109/tip.2022.3162099","pmid":"https://pubmed.ncbi.nlm.nih.gov/35353700"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2022.3162099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3162099","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100649232","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0002-6956-7342"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-6956-7342","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100658200","display_name":"Qilong Wang","orcid":"https://orcid.org/0000-0002-3765-9787"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qilong Wang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-3765-9787","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100776513","display_name":"Hongzhi Zhang","orcid":"https://orcid.org/0000-0001-8025-346X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongzhi Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056686459","display_name":"Qinghua Hu","orcid":"https://orcid.org/0000-0001-7765-8095"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Hu","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-7765-8095","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100636655","display_name":"Wangmeng Zuo","orcid":"https://orcid.org/0000-0002-3330-783X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wangmeng Zuo","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-3330-783X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9364,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.92349062,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"31","issue":null,"first_page":"2962","last_page":"2974"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.779079794883728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7679973840713501},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6713016033172607},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6643748879432678},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6281574964523315},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.6256653070449829},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5581367015838623},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5400288105010986},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5019474029541016},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.49428558349609375},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.47179025411605835},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46743741631507874},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.4305742681026459},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.4226337671279907},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41641050577163696},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40896281599998474},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08259198069572449}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.779079794883728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7679973840713501},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6713016033172607},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6643748879432678},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6281574964523315},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.6256653070449829},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5581367015838623},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5400288105010986},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5019474029541016},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.49428558349609375},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.47179025411605835},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46743741631507874},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.4305742681026459},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.4226337671279907},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41641050577163696},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40896281599998474},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08259198069572449},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2022.3162099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3162099","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:35353700","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35353700","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1068922776","display_name":null,"funder_award_id":"U19A2073","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4013770026","display_name":null,"funder_award_id":"61925602","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7332021516","display_name":null,"funder_award_id":"20JCQNJC1530","funder_id":"https://openalex.org/F4320323993","funder_display_name":"Natural Science Foundation of Tianjin City"},{"id":"https://openalex.org/G8075617114","display_name":null,"funder_award_id":"2019YFB2101901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323993","display_name":"Natural Science Foundation of Tianjin City","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1523723941","https://openalex.org/W1861492603","https://openalex.org/W1996348120","https://openalex.org/W2104657103","https://openalex.org/W2108598243","https://openalex.org/W2116484132","https://openalex.org/W2156303437","https://openalex.org/W2194775991","https://openalex.org/W2288122362","https://openalex.org/W2295107390","https://openalex.org/W2549139847","https://openalex.org/W2565639579","https://openalex.org/W2601564443","https://openalex.org/W2767434619","https://openalex.org/W2798441115","https://openalex.org/W2886904239","https://openalex.org/W2891894830","https://openalex.org/W2895401575","https://openalex.org/W2908510526","https://openalex.org/W2922086296","https://openalex.org/W2934198733","https://openalex.org/W2936614765","https://openalex.org/W2950800384","https://openalex.org/W2956902387","https://openalex.org/W2959581809","https://openalex.org/W2962731685","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2963430933","https://openalex.org/W2963446712","https://openalex.org/W2963927307","https://openalex.org/W2964241181","https://openalex.org/W2964342346","https://openalex.org/W2964444661","https://openalex.org/W2965936015","https://openalex.org/W2970575838","https://openalex.org/W2982770724","https://openalex.org/W2986357608","https://openalex.org/W2988452521","https://openalex.org/W2989604896","https://openalex.org/W2990503944","https://openalex.org/W2995482434","https://openalex.org/W3003964240","https://openalex.org/W3014641072","https://openalex.org/W3034315787","https://openalex.org/W3035396860","https://openalex.org/W3035473155","https://openalex.org/W3035694605","https://openalex.org/W3082489683","https://openalex.org/W3092153824","https://openalex.org/W3097571420","https://openalex.org/W3107473354","https://openalex.org/W3109381875","https://openalex.org/W3120479662","https://openalex.org/W3121570115","https://openalex.org/W3133630855","https://openalex.org/W3138994021","https://openalex.org/W3191338014","https://openalex.org/W4250325771","https://openalex.org/W6631453609","https://openalex.org/W6682864246","https://openalex.org/W6714138976","https://openalex.org/W6745995898","https://openalex.org/W6757817989","https://openalex.org/W6766183005","https://openalex.org/W6766826567","https://openalex.org/W6767109091","https://openalex.org/W6791793911"],"related_works":["https://openalex.org/W2237537322","https://openalex.org/W2950678851","https://openalex.org/W4301248618","https://openalex.org/W2894651257","https://openalex.org/W3200590620","https://openalex.org/W2165343651","https://openalex.org/W2343790552","https://openalex.org/W4200172193","https://openalex.org/W2242427765","https://openalex.org/W2075830955"],"abstract_inverted_index":{"Object":[0],"detection":[1,205],"is":[2,22,189],"usually":[3,59],"solved":[4],"by":[5,102],"learning":[6,17,135],"a":[7,103,130,176,185],"deep":[8],"architecture":[9],"involving":[10],"classification":[11,37,78,149,160,181],"and":[12,38,79,116,150,161,182,193],"localization":[13,39,80,151,162],"tasks,":[14],"where":[15,158],"feature":[16,56,134,186],"for":[18,77,94,113,137,148,174,180,191],"these":[19,95,125],"two":[20,62,96,154,171],"tasks":[21,40,81,98,152],"shared":[23,104],"using":[24,153],"the":[25,42,52,71,92,167,170,203],"same":[26],"backbone":[27,105,156,172],"model.":[28],"Recent":[29],"works":[30],"have":[31],"shown":[32],"that":[33,91,212],"suitable":[34],"disentanglement":[35,57],"of":[36,48,66,169],"has":[41,87],"great":[43],"potential":[44],"to":[45,90,120,201],"improve":[46],"performance":[47],"object":[49,139],"detection.":[50,140],"Despite":[51],"promising":[53],"performance,":[54],"existing":[55],"methods":[58],"suffer":[60],"from":[61],"limitations.":[63],"First,":[64],"most":[65],"them":[67],"only":[68],"focus":[69],"on":[70,208],"disentangled":[72,146],"proposals":[73],"or":[74],"predication":[75],"heads":[76,163],"after":[82],"RPN.":[83,108],"While":[84],"little":[85],"consideration":[86],"been":[88],"given":[89],"features":[93,147,179],"different":[97],"actually":[99],"are":[100,111,117,164,198],"obtained":[101],"model":[106],"before":[107],"Second,":[109],"they":[110],"suggested":[112],"two-stage":[114],"objectors":[115],"not":[118],"applicable":[119],"one-stage":[121,138],"methods.":[122],"To":[123],"overcome":[124],"limitations,":[126],"this":[127],"paper":[128],"presents":[129],"novel":[131],"fully":[132,177],"task-specific":[133,178,195],"method":[136,143,215],"Specifically,":[141],"our":[142,213],"first":[144],"learns":[145],"separated":[155],"models,":[157],"auxiliary":[159],"inserted":[165],"at":[166],"end":[168],"models":[173],"providing":[175],"localization.":[183],"Then,":[184],"interaction":[187],"module":[188],"developed":[190],"aligning":[192],"fusing":[194],"features,":[196],"which":[197],"further":[199],"used":[200],"produce":[202],"final":[204],"result.":[206],"Experiments":[207],"MS":[209],"COCO":[210],"show":[211],"proposed":[214],"(dubbed":[216],"CrabNet)":[217],"can":[218],"achieve":[219],"clear":[220],"improvement":[221],"over":[222],"counterparts":[223],"with":[224],"increasing":[225],"limited":[226],"inference":[227],"time,":[228],"while":[229],"performing":[230],"favorably":[231],"against":[232],"state-of-the-arts.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
