{"id":"https://openalex.org/W7151393226","doi":"https://doi.org/10.1109/icmla66185.2025.00190","title":"Semi-Dense Feature Matching via Mamba-Based Knowledge Distillation","display_name":"Semi-Dense Feature Matching via Mamba-Based Knowledge Distillation","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W7151393226","doi":"https://doi.org/10.1109/icmla66185.2025.00190"},"language":null,"primary_location":{"id":"doi:10.1109/icmla66185.2025.00190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla66185.2025.00190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5084013090","display_name":"Jos\u00e9 Antonio Valero Medina","orcid":"https://orcid.org/0000-0003-1228-0241"},"institutions":[{"id":"https://openalex.org/I56085075","display_name":"University of Tartu","ror":"https://ror.org/03z77qz90","country_code":"EE","type":"education","lineage":["https://openalex.org/I56085075"]}],"countries":["EE"],"is_corresponding":true,"raw_author_name":"Jos\u00e9 Medina","raw_affiliation_strings":["University of Tartu,ITS Lab, Institute of Computer Science,Tartu,Estonia"],"affiliations":[{"raw_affiliation_string":"University of Tartu,ITS Lab, Institute of Computer Science,Tartu,Estonia","institution_ids":["https://openalex.org/I56085075"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133088664","display_name":"Helena Sokk","orcid":null},"institutions":[{"id":"https://openalex.org/I56085075","display_name":"University of Tartu","ror":"https://ror.org/03z77qz90","country_code":"EE","type":"education","lineage":["https://openalex.org/I56085075"]}],"countries":["EE"],"is_corresponding":false,"raw_author_name":"Helena Sokk","raw_affiliation_strings":["University of Tartu,ITS Lab, Institute of Computer Science,Tartu,Estonia"],"affiliations":[{"raw_affiliation_string":"University of Tartu,ITS Lab, Institute of Computer Science,Tartu,Estonia","institution_ids":["https://openalex.org/I56085075"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008068280","display_name":"Amnir Hadachi","orcid":"https://orcid.org/0000-0001-9257-3858"},"institutions":[{"id":"https://openalex.org/I56085075","display_name":"University of Tartu","ror":"https://ror.org/03z77qz90","country_code":"EE","type":"education","lineage":["https://openalex.org/I56085075"]}],"countries":["EE"],"is_corresponding":false,"raw_author_name":"Amnir Hadachi","raw_affiliation_strings":["University of Tartu,ITS Lab, Institute of Computer Science,Tartu,Estonia"],"affiliations":[{"raw_affiliation_string":"University of Tartu,ITS Lab, Institute of Computer Science,Tartu,Estonia","institution_ids":["https://openalex.org/I56085075"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084013090"],"corresponding_institution_ids":["https://openalex.org/I56085075"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.74909929,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1249","last_page":"1254"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.2142000049352646,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.2142000049352646,"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/T10057","display_name":"Face and Expression Recognition","score":0.0869000032544136,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.05249999836087227,"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/feature","display_name":"Feature (linguistics)","score":0.48910000920295715},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46700000762939453},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4438000023365021},{"id":"https://openalex.org/keywords/feature-matching","display_name":"Feature matching","score":0.31520000100135803},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.2840000092983246}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6276000142097473},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.579200029373169},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48910000920295715},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46700000762939453},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.31520000100135803},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29910001158714294},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.265500009059906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2612999975681305},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmla66185.2025.00190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla66185.2025.00190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5587795972824097,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2117228865","https://openalex.org/W2151103935","https://openalex.org/W3034275286","https://openalex.org/W3034368386","https://openalex.org/W3043075211","https://openalex.org/W3049716063","https://openalex.org/W3117234758","https://openalex.org/W3166285241","https://openalex.org/W3179351458","https://openalex.org/W4321231176","https://openalex.org/W4402753714","https://openalex.org/W4407348251","https://openalex.org/W4411245107","https://openalex.org/W4412482713","https://openalex.org/W4413155710","https://openalex.org/W4413917622"],"related_works":[],"abstract_inverted_index":{"Precise":[0],"GIS":[1,109,200],"layers":[2],"are":[3],"essential":[4],"for":[5,212,218],"smart-city":[6],"services":[7],"and":[8,17,83,115,123,138,194],"autonomous":[9],"navigation.":[10],"However,":[11],"pedestrian-level":[12],"assets":[13],"such":[14],"as":[15],"sidewalks":[16],"vegetation":[18],"buffers":[19],"remain":[20],"poorly":[21],"mapped":[22],"in":[23],"most":[24],"urban":[25,224],"databases.":[26],"AI-generated":[27,183],"imagery":[28],"offers":[29],"a":[30,52,92,96,101,141],"way":[31,217],"to":[32,169],"complement":[33],"these":[34],"datasets,":[35],"but":[36],"only":[37],"if":[38],"its":[39],"synthesised":[40],"views":[41],"can":[42],"be":[43],"accurately":[44],"aligned.":[45],"To":[46],"address":[47],"this":[48],"challenge,":[49],"we":[50],"introduce":[51],"feature-to-feature":[53],"knowledge":[54],"distillation":[55],"(KD)":[56],"framework":[57,87],"that":[58,79,221],"produces":[59],"an":[60,125],"ultra-lightweight":[61],"neural":[62],"network":[63],"(student)":[64],"capable":[65],"of":[66,182,191],"extracting":[67],"semi-dense":[68],"features":[69,73],"from":[70,91,165],"images.":[71],"These":[72,162],"yield":[74],"semantically":[75],"rich":[76],"keypoint":[77],"correspondences":[78],"support":[80,222],"translation,":[81],"rotation,":[82],"scale":[84],"restoration.":[85],"The":[86,117,130,202],"distils":[88],"geometric":[89,172],"expertise":[90],"high-capacity":[93],"teacher":[94],"into":[95,197],"compact":[97],"student,":[98],"built":[99],"on":[100,107],"Mamba":[102],"model.":[103],"Our":[104],"evaluation":[105],"focuses":[106],"aligning":[108],"features,":[110],"covering":[111],"roads,":[112],"sidewalks,":[113],"buildings,":[114],"vegetation.":[116],"KD-Mamba":[118],"matcher":[119],"boosts":[120],"alignment":[121],"accuracy":[122],"reaches":[124],"86%":[126],"post-correction":[127],"similarity":[128],"rate.":[129],"proposed":[131],"method":[132],"outperforms":[133],"classical":[134],"feature-based":[135],"baselines,":[136],"SIFT":[137],"ORB,":[139],"by":[140,160],"wide":[142],"margin":[143],"(around":[144],"12%).":[145],"Compared":[146],"with":[147,174],"state-of-the-art":[148],"deep":[149],"homography":[150],"estimators,":[151],"it":[152],"achieves":[153],"similar":[154],"precision":[155],"while":[156],"cutting":[157],"computational":[158],"cost":[159],"40%.":[161],"gains":[163],"stem":[164],"the":[166,179,188,216],"model\u2019s":[167],"ability":[168],"capture":[170],"long-range":[171],"dependencies":[173],"$\\mathcal{O}(N)$":[175],"complexity.":[176],"By":[177],"tightening":[178],"spatial":[180],"registration":[181],"imagery,":[184],"our":[185],"approach":[186],"enables":[187],"reliable":[189],"fusion":[190],"street-level,":[192],"aerial,":[193],"satellite":[195],"data":[196],"coherent":[198],"pedestrian":[199],"layers.":[201],"implementation":[203],"is":[204],"publicly":[205],"available":[206],"at":[207],"https://github.com/JoseLMedinaC/FeatMatchGIS,":[208],"providing":[209],"open":[210],"access":[211],"reproducibility.":[213],"This":[214],"paves":[215],"high-fidelity":[219],"maps":[220],"next-generation":[223],"applications.":[225]},"counts_by_year":[],"updated_date":"2026-04-09T06:08:40.794217","created_date":"2026-04-08T00:00:00"}