{"id":"https://openalex.org/W7167111802","doi":"https://doi.org/10.48550/arxiv.2607.00752","title":"GKDT: General Keypoint Detection Transformer","display_name":"GKDT: General Keypoint Detection Transformer","publication_year":2026,"publication_date":"2026-07-01","ids":{"openalex":"https://openalex.org/W7167111802","doi":"https://doi.org/10.48550/arxiv.2607.00752"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.00752","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00752","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.00752","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139868681","display_name":"Changsheng Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Changsheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139869865","display_name":"Yuxin Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yuxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119949440","display_name":"Haokun Gui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gui, Haokun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139915975","display_name":"Rong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Rong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139889388","display_name":"Jie Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139917328","display_name":"Harry Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Harry","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139872078","display_name":"Anton van den Hengel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hengel, Anton van den","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139914610","display_name":"Jiaya Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Jiaya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.810699999332428,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.810699999332428,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.12099999934434891,"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/T10028","display_name":"Topic Modeling","score":0.010300000198185444,"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/generality","display_name":"Generality","score":0.8382999897003174},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6593000292778015},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.6504999995231628},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.412200003862381},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.39329999685287476},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.357699990272522}],"concepts":[{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.8382999897003174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7310000061988831},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6593000292778015},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.6504999995231628},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5764999985694885},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.412200003862381},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.39329999685287476},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36719998717308044},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.357699990272522},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3287000060081482},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3188999891281128},{"id":"https://openalex.org/C2982832238","wikidata":"https://www.wikidata.org/wiki/Q5531640","display_name":"General purpose","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3089999854564667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3021000027656555},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.00752","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00752","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.00752","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00752","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1,40],"emergence":[2],"of":[3,21,59,116],"various":[4],"pre-trained":[5],"vision":[6,11],"and":[7,70,88,124,146,171],"language":[8],"models,":[9,170],"computer":[10],"is":[12,57],"shifting":[13],"from":[14,66],"narrow-domain":[15],"to":[16,31,165],"open-domain":[17],"recognition.":[18],"The":[19,55,168],"construction":[20],"a":[22,48,85,114],"more":[23],"powerful":[24,89],"yet":[25],"general":[26],"keypoint":[27,51,76],"detection":[28],"(GKD)":[29],"model":[30,93,109,142],"support":[32],"diverse":[33,63],"tasks":[34],"has":[35],"become":[36],"increasingly":[37],"important":[38],"in":[39,148],"field.":[41],"To":[42,107],"this":[43],"end,":[44],"we":[45,82,111],"firstly":[46],"present":[47],"large-scale":[49],"unified":[50,73],"dataset":[52,56],"called":[53],"MegaKPT.":[54],"composed":[58],"over":[60,130,157],"1.3":[61],"million":[62],"object":[64],"instances":[65],"twenty-nine":[67],"existing":[68],"datasets,":[69],"enjoys":[71],"high-quality":[72],"annotations":[74],"with":[75,134,154],"text":[77,103],"descriptions.":[78],"Based":[79],"on":[80,151],"MegaKPT,":[81],"develop":[83],"GKDT,":[84],"simple,":[86],"flexible":[87],"DINOv3":[90],"based":[91],"Transformer":[92],"for":[94],"General":[95],"Keypoint":[96],"Detection.":[97],"Our":[98],"GKDT":[99,141],"supports":[100],"visual":[101],"prompts,":[102,104],"or":[105,136],"both.":[106],"enhance":[108],"training,":[110],"also":[112],"propose":[113],"suite":[115],"useful":[117],"strategies":[118],"such":[119],"as":[120],"mix-modal":[121],"prompted":[122],"training":[123],"dynamic":[125],"importance":[126],"sampling.":[127],"By":[128],"testing":[129],"22":[131],"test":[132],"sets":[133],"seen":[135],"unseen":[137],"objects,":[138],"our":[139],"single":[140],"shows":[143],"strong":[144],"performance":[145],"generality":[147],"detecting":[149],"keypoints":[150],"broad":[152],"categories,":[153],"most":[155],"categories":[156],"90\\%":[158],"PCK@0.1":[159],"accuracy,":[160],"offering":[161],"high":[162],"practical":[163],"applicability":[164],"real-world":[166],"problems.":[167],"dataset,":[169],"codes":[172],"will":[173],"be":[174],"released":[175],"at":[176],"https://github.com/AlanLuSun/General-Keypoint-Detection.":[177]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-03T00:00:00"}