{"id":"https://openalex.org/W7166648021","doi":"https://doi.org/10.48550/arxiv.2606.30408","title":"SA-Homo: Scale Adaptive Homography Estimation for Scale Variation Scenarios","display_name":"SA-Homo: Scale Adaptive Homography Estimation for Scale Variation Scenarios","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166648021","doi":"https://doi.org/10.48550/arxiv.2606.30408"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.30408","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30408","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":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.2606.30408","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139663089","display_name":"Shangxuan Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Shangxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113485823","display_name":"H. Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Haifeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139666690","display_name":"Yuhang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043514827","display_name":"Huarong Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Huarong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139697494","display_name":"Wen Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Wen","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.36250001192092896,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.36250001192092896,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"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":0.2517000138759613,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.11289999634027481,"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/scale","display_name":"Scale (ratio)","score":0.6177999973297119},{"id":"https://openalex.org/keywords/homography","display_name":"Homography","score":0.5978999733924866},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5209000110626221},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4814000129699707},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47699999809265137},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4124999940395355},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.40290001034736633},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.38530001044273376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.629800021648407},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6177999973297119},{"id":"https://openalex.org/C28751775","wikidata":"https://www.wikidata.org/wiki/Q2112539","display_name":"Homography","level":4,"score":0.5978999733924866},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5209000110626221},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5063999891281128},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4814000129699707},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47699999809265137},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.40290001034736633},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.38530001044273376},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3562999963760376},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3382999897003174},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33320000767707825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3181999921798706},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.30559998750686646},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C2779982483","wikidata":"https://www.wikidata.org/wiki/Q6094420","display_name":"Iterative refinement","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.259799987077713},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.25270000100135803},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.30408","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30408","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.30408","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30408","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Homography":[0,160],"estimation,":[1],"as":[2,39],"one":[3],"of":[4,79],"the":[5,93,111,151,167,178],"fundamental":[6],"problems":[7],"in":[8,36,207],"computer":[9],"vision,":[10],"remains":[11],"challenged":[12],"by":[13],"scale":[14,23,56,80,87,146,153,202,214],"variation":[15,215],"scenarios":[16,211],"where":[17],"image":[18],"pairs":[19],"potentially":[20],"exhibit":[21],"significant":[22,33],"discrepancies.":[24],"Existing":[25],"deep":[26],"learning":[27],"frameworks":[28],"frequently":[29],"suffer":[30],"from":[31,92],"a":[32,64,76,85,97,101,105,122,138,157,181],"performance":[34],"degradation":[35],"such":[37],"cases,":[38],"they":[40],"rely":[41],"on":[42],"limited":[43],"displacement":[44],"assumptions":[45],"and":[46,132,212,218],"local":[47,102,170],"feature":[48,134],"consistency":[49],"that":[50,90,194],"might":[51],"not":[52],"hold":[53],"under":[54,200],"large":[55],"gaps.":[57],"In":[58],"this":[59,174],"paper,":[60],"we":[61,109,176],"propose":[62],"SA-Homo,":[63],"novel":[65],"scale-adaptive":[66],"homography":[67],"estimation":[68],"framework":[69],"designed":[70],"to":[71,100,128],"achieve":[72],"robust":[73,147],"alignment":[74,88],"across":[75],"wide":[77],"range":[78],"discrepancy":[81],"ratios.":[82],"We":[83],"adopt":[84],"hierarchical":[86],"strategy":[89],"transitions":[91],"global":[94,139],"perspective":[95,103],"with":[96,104,137],"heavy":[98],"module":[99],"light":[106],"module.":[107],"Specifically,":[108],"introduce":[110],"Scale-aware":[112],"Discrepancy":[113],"Bridging":[114],"Module":[115,163],"(SDBM)":[116],"for":[117,145,188],"initial":[118,152],"alignment,":[119],"which":[120],"utilizes":[121],"Multi-scale":[123],"Linear":[124],"Attention":[125],"Cascade":[126],"(MLAC)":[127],"capture":[129],"long-range":[130],"dependencies":[131],"mitigate":[133],"inconsistencies,":[135],"along":[136],"Cross-scale":[140],"Similarity":[141],"Matrix":[142],"Block":[143],"(CSMB)":[144],"correlation":[148],"representation.":[149],"Once":[150],"gap":[154],"is":[155],"bridged,":[156],"lightweight":[158],"Iterative":[159],"Estimation":[161],"Refinement":[162],"(IHERM)":[164],"progressively":[165],"polishes":[166],"result":[168],"using":[169],"correlations.":[171],"To":[172],"facilitate":[173],"research,":[175],"contribute":[177],"HMSA":[179],"dataset,":[180],"high-resolution,":[182],"multi-modal":[183],"satellite":[184],"benchmark":[185],"specifically":[186],"tailored":[187],"scale-variant":[189],"challenges.":[190],"Extensive":[191],"experiments":[192],"demonstrate":[193],"SA-Homo":[195],"maintains":[196],"high":[197],"precision":[198],"even":[199],"8$\\times$":[201],"discrepancies,":[203],"outperforming":[204],"state-of-the-art":[205],"methods":[206],"both":[208],"conventional":[209],"scale-similar":[210],"challenging":[213],"scenarios.":[216],"Code":[217],"collected":[219],"datasets":[220],"are":[221],"available":[222],"at":[223],"https://github.com/shangxuanx330/SA_Homo":[224]},"counts_by_year":[],"updated_date":"2026-07-01T06:29:00.853634","created_date":"2026-07-01T00:00:00"}