{"id":"https://openalex.org/W4414930176","doi":"https://doi.org/10.1145/3746027.3755452","title":"LIDAR: Lightweight Adaptive Cue-Aware Fusion Vision Mamba for Multimodal Segmentation of Structural Cracks","display_name":"LIDAR: Lightweight Adaptive Cue-Aware Fusion Vision Mamba for Multimodal Segmentation of Structural Cracks","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4414930176","doi":"https://doi.org/10.1145/3746027.3755452"},"language":"en","primary_location":{"id":"doi:10.1145/3746027.3755452","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.22477","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Hui Liu","orcid":"https://orcid.org/0009-0009-5742-0202"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Liu","raw_affiliation_strings":["Tianjin University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0009-5742-0202","affiliations":[{"raw_affiliation_string":"Tianjin University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chen Jia","orcid":"https://orcid.org/0000-0002-7535-479X"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Jia","raw_affiliation_strings":["Tianjin University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-7535-479X","affiliations":[{"raw_affiliation_string":"Tianjin University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007910454","display_name":"Fan Shi","orcid":"https://orcid.org/0000-0003-2074-0228"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Shi","raw_affiliation_strings":["Tianjin University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-2074-0228","affiliations":[{"raw_affiliation_string":"Tianjin University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xu Cheng","orcid":"https://orcid.org/0000-0002-4724-5748"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Cheng","raw_affiliation_strings":["Tianjin University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-4724-5748","affiliations":[{"raw_affiliation_string":"Tianjin University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091786800","display_name":"Mengfei Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengfei Shi","raw_affiliation_strings":["Tianjin University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0006-3761-1931","affiliations":[{"raw_affiliation_string":"Tianjin University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xia Xie","orcid":"https://orcid.org/0009-0002-6890-3663"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xia Xie","raw_affiliation_strings":["Hainan University, Haikou, China"],"raw_orcid":"https://orcid.org/0009-0002-6890-3663","affiliations":[{"raw_affiliation_string":"Hainan University, Haikou, China","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055627037","display_name":"Shengyong Chen","orcid":"https://orcid.org/0000-0002-6705-3831"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengyong Chen","raw_affiliation_strings":["Tianjin University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-6705-3831","affiliations":[{"raw_affiliation_string":"Tianjin University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I136765683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"1832","last_page":"1841"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11850","display_name":"Concrete Corrosion and Durability","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.9711999893188477,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7074000239372253},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5231000185012817},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5231000185012817},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4318000078201294},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4205000102519989},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4154999852180481},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.37770000100135803},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37290000915527344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7445999979972839},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7074000239372253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6872000098228455},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5738000273704529},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5231000185012817},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5231000185012817},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4318000078201294},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37290000915527344},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.362199991941452},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.35179999470710754},{"id":"https://openalex.org/C2780757906","wikidata":"https://www.wikidata.org/wiki/Q5276676","display_name":"Dilation (metric space)","level":2,"score":0.3449000120162964},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3746027.3755452","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2507.22477","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.22477","pdf_url":"https://arxiv.org/pdf/2507.22477","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.22477","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.22477","pdf_url":"https://arxiv.org/pdf/2507.22477","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3103790921","display_name":null,"funder_award_id":"62272342, 62020106004, 62306212, T2422015","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Achieving":[0],"pixel-level":[1,65],"segmentation":[2,16,67],"with":[3,146,184],"low":[4],"computational":[5,148],"cost":[6],"using":[7],"multimodal":[8,60],"data":[9],"remains":[10],"a":[11,39,74,84,118,134],"key":[12],"challenge":[13],"in":[14,154,178,182],"crack":[15,61,66,96],"tasks.":[17],"Existing":[18],"methods":[19],"lack":[20],"the":[21,99,170],"capability":[22],"for":[23],"adaptive":[24],"perception":[25],"and":[26,50,53,83,117,126,180,189],"efficient":[27],"interactive":[28],"fusion":[29,120],"of":[30,73],"cross-modal":[31],"features.":[32],"To":[33],"address":[34],"these":[35],"challenges,":[36],"we":[37,132],"propose":[38],"Lightweight":[40,75,85,135],"Adaptive":[41,76,112],"Cue-Aware":[42,77],"Vision":[43],"Mamba":[44],"network":[45],"(LIDAR),":[46],"which":[47],"efficiently":[48],"perceives":[49],"integrates":[51],"morphological":[52,144],"textural":[54],"cues":[55,97,128],"from":[56],"different":[57],"modalities":[58],"under":[59],"scenarios,":[62],"generating":[63],"clear":[64],"maps.":[68],"Specifically,":[69],"LIDAR":[70],"is":[71],"composed":[72],"Visual":[78],"State":[79],"Space":[80],"module":[81,91],"(LacaVSS)":[82],"Dual":[86],"Domain":[87,114],"Dynamic":[88,103],"Collaborative":[89],"Fusion":[90],"(LD3CF).":[92],"LacaVSS":[93],"adaptively":[94],"models":[95],"through":[98],"proposed":[100],"mask-guided":[101],"Efficient":[102],"Guided":[104],"Scanning":[105],"Strategy":[106],"(EDG-SS),":[107],"while":[108],"LD3CF":[109],"leverages":[110],"an":[111],"Frequency":[113],"Perceptron":[115],"(AFDP)":[116],"dual-pooling":[119],"strategy":[121],"to":[122,141],"effectively":[123],"capture":[124],"spatial":[125],"frequency-domain":[127],"across":[129],"modalities.":[130],"Moreover,":[131],"design":[133],"Dynamically":[136],"Modulated":[137],"Multi-Kernel":[138],"convolution":[139],"(LDMK)":[140],"perceive":[142],"complex":[143],"structures":[145],"minimal":[147],"overhead,":[149],"replacing":[150],"most":[151],"convolutional":[152],"operations":[153],"LIDAR.":[155],"Experiments":[156],"on":[157],"three":[158],"datasets":[159,190],"demonstrate":[160],"that":[161],"our":[162,174],"method":[163,175],"outperforms":[164],"other":[165],"state-of-the-art":[166],"(SOTA)":[167],"methods.":[168],"On":[169],"light-field":[171],"depth":[172],"dataset,":[173],"achieves":[176],"0.8204":[177],"F1":[179],"0.8465":[181],"mIoU":[183],"only":[185],"5.35M":[186],"parameters.":[187],"Code":[188],"are":[191],"available":[192],"at":[193],"https://github.com/Karl1109/LIDAR-Mamba.":[194]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}