{"id":"https://openalex.org/W4411635490","doi":"https://doi.org/10.1145/3731715.3733397","title":"MSSA-Net: A Multi-Scale Structure-Aware Network for Edge Detection in Point Clouds","display_name":"MSSA-Net: A Multi-Scale Structure-Aware Network for Edge Detection in Point Clouds","publication_year":2025,"publication_date":"2025-06-25","ids":{"openalex":"https://openalex.org/W4411635490","doi":"https://doi.org/10.1145/3731715.3733397"},"language":"en","primary_location":{"id":"doi:10.1145/3731715.3733397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3731715.3733397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Multimedia Retrieval","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/A5101244926","display_name":"Yunzhou Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunzhou Xia","raw_affiliation_strings":["Xiamen University, Xiamen, Fujian, China"],"raw_orcid":"https://orcid.org/0009-0007-8681-0440","affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, Fujian, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084541481","display_name":"Weiqi Yan","orcid":"https://orcid.org/0000-0003-3349-6869"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiqi Yan","raw_affiliation_strings":["Xiamen University, Xiamen, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0003-3349-6869","affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, Fujian, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002805753","display_name":"Yu Zang","orcid":"https://orcid.org/0000-0002-7193-1414"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zang","raw_affiliation_strings":["Xiamen University, Xiamen, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0002-7193-1414","affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, Fujian, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066301734","display_name":"Weiquan Liu","orcid":"https://orcid.org/0000-0002-5934-1139"},"institutions":[{"id":"https://openalex.org/I161346416","display_name":"Jimei University","ror":"https://ror.org/03hknyb50","country_code":"CN","type":"education","lineage":["https://openalex.org/I161346416"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiquan Liu","raw_affiliation_strings":["Jimei University, Xiamen, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0002-5934-1139","affiliations":[{"raw_affiliation_string":"Jimei University, Xiamen, Fujian, China","institution_ids":["https://openalex.org/I161346416"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100416961","display_name":"Cheng Wang","orcid":"https://orcid.org/0000-0001-6075-796X"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Wang","raw_affiliation_strings":["Xiamen University, Xiamen, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0001-6075-796X","affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, Fujian, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13528389,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1526","last_page":"1534"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6698523759841919},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.616635799407959},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5403658747673035},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5391440987586975},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5343624353408813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21325570344924927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07254844903945923},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0665026605129242},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06547695398330688},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.05719384551048279}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6698523759841919},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.616635799407959},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5403658747673035},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5391440987586975},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5343624353408813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21325570344924927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07254844903945923},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0665026605129242},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06547695398330688},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.05719384551048279}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3731715.3733397","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3731715.3733397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1965722128","https://openalex.org/W2019732471","https://openalex.org/W2112477742","https://openalex.org/W2131723805","https://openalex.org/W2149668583","https://openalex.org/W2151049637","https://openalex.org/W2249153497","https://openalex.org/W2460657278","https://openalex.org/W2467615243","https://openalex.org/W2512257441","https://openalex.org/W2594519801","https://openalex.org/W2621534427","https://openalex.org/W2625290171","https://openalex.org/W2767814567","https://openalex.org/W2884154111","https://openalex.org/W2890901115","https://openalex.org/W2960986959","https://openalex.org/W2972931660","https://openalex.org/W3012494314","https://openalex.org/W3041557920","https://openalex.org/W3174510152","https://openalex.org/W3174578140","https://openalex.org/W4214755140","https://openalex.org/W4225371802","https://openalex.org/W4236965008","https://openalex.org/W4241602464","https://openalex.org/W4286611309","https://openalex.org/W4287585720","https://openalex.org/W4365152882","https://openalex.org/W4384080551","https://openalex.org/W4385535012","https://openalex.org/W4385815517","https://openalex.org/W4386076534","https://openalex.org/W4386766976","https://openalex.org/W4387928000","https://openalex.org/W6780528297"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4389574804"],"abstract_inverted_index":{"Edge":[0],"detection":[1,21,40],"in":[2,9,83,165,184],"point":[3,164,167],"clouds":[4],"is":[5,99],"a":[6,23,92,197],"fundamental":[7],"problem":[8],"3D":[10],"vision.":[11],"Previous":[12],"approaches":[13],"based":[14],"on":[15,54,87,204],"point-based":[16],"neural":[17],"networks":[18],"treat":[19],"edge":[20,39,62],"as":[22,57,59],"binary":[24],"segmentation":[25,30],"task,":[26],"directly":[27],"applying":[28],"semantic":[29,42],"frameworks.":[31],"However,":[32],"due":[33],"to":[34,49,156,177],"the":[35,134,158,166,171],"intrinsic":[36],"differences":[37],"between":[38],"and":[41,80,127,200],"segmentation,":[43],"these":[44,67,88],"methods":[45,51],"have":[46],"limitations":[47],"compared":[48],"traditional":[50],"that":[52,190],"rely":[53],"hand-crafted":[55],"features,":[56,179],"well":[58],"recent":[60],"volumetric":[61],"representation":[63],"methods.":[64],"To":[65],"address":[66],"challenges,":[68],"we":[69,90],"propose":[70],"three":[71],"key":[72],"constraints:":[73],"Local":[74,124],"Structure":[75,125],"Disruption,":[76],"Encoding":[77,128],"Region":[78,129],"Offset,":[79],"Information":[81,182],"Loss":[82,183],"Feature":[84,185],"Propagation.":[85,186],"Based":[86],"constraints,":[89],"introduce":[91],"novel":[93],"Multi-Scale":[94],"Structure-Aware":[95],"Network":[96],"(MSSA-Net).":[97],"MSSA-Net":[98,169,192],"designed":[100],"around":[101],"local":[102,107,150,159],"multi-scale":[103,149],"neighborhoods,":[104],"learning":[105],"intact":[106],"structural":[108,151,160],"features":[109,152,176],"at":[110],"different":[111,143],"scales":[112,144],"within":[113],"highly":[114],"relevant":[115],"neighborhoods":[116],"for":[117,142,173],"each":[118,163],"point.":[119],"This":[120],"strategy":[121],"effectively":[122],"avoids":[123],"Disruption":[126],"Offset.":[130],"During":[131],"feature":[132],"learning,":[133],"MSSA":[135],"Core":[136],"module":[137],"generates":[138],"adaptive":[139],"encoding":[140],"branches":[141],"of":[145,162],"neighborhoods.":[146],"The":[147],"learned":[148],"are":[153],"then":[154],"concatenated":[155],"encode":[157],"information":[161],"cloud.":[168],"eliminates":[170],"need":[172],"propagating":[174],"high-level":[175],"low-level":[178],"thereby":[180],"preventing":[181],"Extensive":[187],"experiments":[188],"demonstrate":[189],"our":[191],"surpasses":[193],"existing":[194],"works":[195],"by":[196],"large":[198],"margin":[199],"achieves":[201],"state-of-the-art":[202],"performance":[203],"various":[205],"datasets.":[206]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
