{"id":"https://openalex.org/W7129436022","doi":"https://doi.org/10.48550/arxiv.2602.13728","title":"Explore Intrinsic Geometry for Query-based Tiny and Oriented Object Detector with Momentum-based Bipartite Matching","display_name":"Explore Intrinsic Geometry for Query-based Tiny and Oriented Object Detector with Momentum-based Bipartite Matching","publication_year":2026,"publication_date":"2026-02-14","ids":{"openalex":"https://openalex.org/W7129436022","doi":"https://doi.org/10.48550/arxiv.2602.13728"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.13728","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126273704","display_name":"Junpeng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Junpeng","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126189155","display_name":"Zewei Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zewei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126209806","display_name":"Jie Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Jie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126195732","display_name":"Yuhui Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Yuhui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126236453","display_name":"Ronghua Shang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shang, Ronghua","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101539518","display_name":"Mengxuan Zhang","orcid":"https://orcid.org/0000-0002-5794-0779"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Mengxuan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5126273704"],"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/T10036","display_name":"Advanced Neural Network Applications","score":0.572700023651123,"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":0.572700023651123,"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":0.3698999881744385,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.004999999888241291,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.670799970626831},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6324999928474426},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5849999785423279},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5698000192642212},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5206999778747559},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5008000135421753},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.47920000553131104},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.4196000099182129},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41440001130104065},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.36039999127388}],"concepts":[{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.670799970626831},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6324999928474426},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5849999785423279},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5698000192642212},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5206999778747559},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5008000135421753},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4805000126361847},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.47920000553131104},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.460999995470047},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45509999990463257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42170000076293945},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41440001130104065},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3734999895095825},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.36039999127388},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.35260000824928284},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33390000462532043},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.3328000009059906},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.33250001072883606},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.29159998893737793},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C23379248","wikidata":"https://www.wikidata.org/wiki/Q200904","display_name":"Epipolar geometry","level":3,"score":0.2858000099658966},{"id":"https://openalex.org/C155745195","wikidata":"https://www.wikidata.org/wiki/Q1164179","display_name":"Comparator","level":3,"score":0.28279998898506165},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2800000011920929},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C40636538","wikidata":"https://www.wikidata.org/wiki/Q81392","display_name":"Fractal","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C93058836","wikidata":"https://www.wikidata.org/wiki/Q1453572","display_name":"Chain code","level":3,"score":0.2590000033378601},{"id":"https://openalex.org/C32990609","wikidata":"https://www.wikidata.org/wiki/Q306542","display_name":"Transformation geometry","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C72545166","wikidata":"https://www.wikidata.org/wiki/Q10866593","display_name":"3-dimensional matching","level":4,"score":0.2551000118255615},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.13728","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.13728","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.13728","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.13728","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"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":{"Recent":[0],"query-based":[1,61],"detectors":[2],"have":[3],"achieved":[4],"remarkable":[5],"progress,":[6],"yet":[7],"their":[8,102],"performance":[9],"remains":[10],"constrained":[11],"when":[12],"handling":[13],"objects":[14,21],"with":[15,141],"arbitrary":[16],"orientations,":[17],"especially":[18],"for":[19,166],"tiny":[20],"capturing":[22],"limited":[23],"texture":[24],"information.":[25],"This":[26],"limitation":[27],"primarily":[28],"stems":[29],"from":[30,101,151],"the":[31,41,87,106,110,161,183],"underutilization":[32],"of":[33,43,109,163,175],"intrinsic":[34,68],"geometry":[35,69],"during":[36],"pixel-based":[37],"feature":[38,71],"decoding":[39,72],"and":[40,73,157],"occurrence":[42],"inter-stage":[44,75,152],"matching":[45,76,133,153],"inconsistency":[46],"caused":[47],"by":[48,95,135],"stage-wise":[49],"bipartite":[50],"matching.":[51],"To":[52],"tackle":[53],"these":[54],"challenges,":[55],"we":[56,79],"present":[57],"IGOFormer,":[58],"a":[59,114,122],"novel":[60],"oriented":[62,168],"object":[63,93,169],"detector":[64],"that":[65],"explicitly":[66],"integrates":[67],"into":[70,118],"enhances":[74,86],"stability.":[77],"Specifically,":[78],"design":[80],"an":[81,92,137,172],"Intrinsic":[82],"Geometry-aware":[83],"Decoder,":[84],"which":[85],"object-related":[88],"features":[89],"conditioned":[90],"on":[91,177],"query":[94],"injecting":[96],"complementary":[97],"geometric":[98,107,116],"embeddings":[99],"extrapolated":[100],"correlations":[103],"to":[104,129],"capture":[105],"layout":[108],"object,":[111],"thereby":[112],"offering":[113],"critical":[115],"insight":[117],"its":[119],"orientation.":[120],"Meanwhile,":[121],"Momentum-based":[123],"Bipartite":[124],"Matching":[125],"scheme":[126],"is":[127],"developed":[128],"adaptively":[130],"aggregate":[131],"historical":[132],"costs":[134],"formulating":[136],"exponential":[138],"moving":[139],"average":[140],"query-specific":[142],"smoothing":[143],"factors,":[144],"effectively":[145],"preventing":[146],"conflicting":[147],"supervisory":[148],"signals":[149],"arising":[150],"inconsistency.":[154],"Extensive":[155],"experiments":[156],"ablation":[158],"studies":[159],"demonstrate":[160],"superiority":[162],"our":[164],"IGOFormer":[165],"aerial":[167],"detection,":[170],"achieving":[171],"AP$_{50}$":[173],"score":[174],"78.00\\%":[176],"DOTA-V1.0":[178],"using":[179],"Swin-T":[180],"backbone":[181],"under":[182],"single-scale":[184],"setting.":[185],"The":[186],"code":[187],"will":[188],"be":[189],"made":[190],"publicly":[191],"available.":[192]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-18T00:00:00"}