{"id":"https://openalex.org/W4415707871","doi":"https://doi.org/10.1109/icme59968.2025.11208950","title":"Unified Line Segment Detection and Description","display_name":"Unified Line Segment Detection and Description","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415707871","doi":"https://doi.org/10.1109/icme59968.2025.11208950"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11208950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11208950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","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/A5021528853","display_name":"Xinyu Lin","orcid":"https://orcid.org/0000-0003-0304-8993"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyu Lin","raw_affiliation_strings":["University of Electronic Science and Technology of China,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102803061","display_name":"Yingjie Zhou","orcid":"https://orcid.org/0009-0007-6864-6691"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjie Zhou","raw_affiliation_strings":["Sichuan University,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"Sichuan University,Chengdu,China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101922422","display_name":"Zhen Long","orcid":"https://orcid.org/0000-0002-1772-916X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Long","raw_affiliation_strings":["University of Electronic Science and Technology of China,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100610065","display_name":"Yipeng Liu","orcid":"https://orcid.org/0000-0003-2084-8781"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yipeng Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101946928","display_name":"Yang Lu","orcid":"https://orcid.org/0000-0003-2368-7856"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Yang","raw_affiliation_strings":["University of Electronic Science and Technology of China,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100301234","display_name":"Ce Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ce Zhu","raw_affiliation_strings":["University of Electronic Science and Technology of China,Chengdu,China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5021528853"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.336573,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.8140000104904175,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.8140000104904175,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.03869999945163727,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.027300000190734863,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/line-segment","display_name":"Line segment","score":0.7573000192642212},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.6732000112533569},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6166999936103821},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5881999731063843},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4505000114440918},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4309000074863434}],"concepts":[{"id":"https://openalex.org/C182124507","wikidata":"https://www.wikidata.org/wiki/Q166154","display_name":"Line segment","level":2,"score":0.7573000192642212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7089999914169312},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.6732000112533569},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6166999936103821},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5881999731063843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.506600022315979},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4505000114440918},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4327999949455261},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4309000074863434},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4115999937057495},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.3635999858379364},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.26030001044273376}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11208950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11208950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","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":47,"referenced_works":["https://openalex.org/W1974880733","https://openalex.org/W1977442558","https://openalex.org/W2008849352","https://openalex.org/W2014710139","https://openalex.org/W2021278996","https://openalex.org/W2048710758","https://openalex.org/W2057710539","https://openalex.org/W2064806997","https://openalex.org/W2068341180","https://openalex.org/W2119605622","https://openalex.org/W2155912251","https://openalex.org/W2160072137","https://openalex.org/W2177274842","https://openalex.org/W2343416886","https://openalex.org/W2571981115","https://openalex.org/W2577678996","https://openalex.org/W2616866739","https://openalex.org/W2737353725","https://openalex.org/W2798943056","https://openalex.org/W2917141083","https://openalex.org/W2965877627","https://openalex.org/W2981415272","https://openalex.org/W3003913300","https://openalex.org/W3012503056","https://openalex.org/W3092685717","https://openalex.org/W3107016113","https://openalex.org/W3123089514","https://openalex.org/W3155554509","https://openalex.org/W3167259153","https://openalex.org/W3200771231","https://openalex.org/W4205353719","https://openalex.org/W4214568521","https://openalex.org/W4214820331","https://openalex.org/W4225985159","https://openalex.org/W4283791382","https://openalex.org/W4312365313","https://openalex.org/W4320713210","https://openalex.org/W4372185026","https://openalex.org/W4372260213","https://openalex.org/W4375809593","https://openalex.org/W4384135348","https://openalex.org/W4386083120","https://openalex.org/W4386495257","https://openalex.org/W4388469655","https://openalex.org/W4390872683","https://openalex.org/W4396909895","https://openalex.org/W4402981490"],"related_works":[],"abstract_inverted_index":{"Line":[0,43],"segments":[1,117],"are":[2],"fundamental":[3],"elements":[4],"in":[5,104],"computer":[6],"vision.":[7],"However,":[8],"aside":[9],"from":[10,78,118],"a":[11,39,111],"few":[12],"computationally":[13],"expensive":[14],"deep":[15,135],"learning-based":[16,129,136],"methods,":[17],"most":[18],"existing":[19],"approaches":[20],"treat":[21],"their":[22,75,102],"detection":[23,66],"and":[24,33,46,67,74,101,131],"description":[25,68],"as":[26],"independent":[27],"tasks,":[28],"leading":[29],"to":[30,62,120],"redundant":[31],"computations":[32],"suboptimal":[34],"performance.":[35],"This":[36],"paper":[37],"introduces":[38],"Unified":[40],"approach":[41],"for":[42,50],"Segment":[44],"Detection":[45],"Description":[47],"(ULSD2),":[48],"designed":[49],"real-time":[51],"vision":[52],"tasks":[53],"with":[54,133],"minimal":[55],"computational":[56],"overhead.":[57],"The":[58,142],"core":[59],"insight":[60],"is":[61,144],"unify":[63],"line":[64,87,116],"segment":[65],"by":[69],"analyzing":[70],"dedicated":[71],"level":[72,99],"lines":[73,100],"differences,":[76],"derived":[77],"gradients,":[79],"which":[80],"effectively":[81],"capture":[82],"the":[83,92,96],"intrinsic":[84],"characteristics":[85],"of":[86,91,98],"segments.":[88],"Furthermore,":[89],"instead":[90],"traditional":[93],"scalar-based":[94],"description,":[95],"use":[97],"differences":[103],"local":[105],"patches":[106],"across":[107],"multiple":[108],"granularities":[109],"enables":[110],"vectorized":[112],"representation":[113],"that":[114,124],"encodes":[115],"coarse":[119],"fine.":[121],"Experiments":[122],"demonstrate":[123],"ULSD2":[125],"outperforms":[126],"other":[127],"non-deep":[128],"methods":[130,137],"competes":[132],"state-of-the-art":[134],"while":[138],"significantly":[139],"improving":[140],"efficiency.":[141],"code":[143],"available":[145],"at":[146],"https://github.com/roylin1229/ULSD2.":[147]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-30T00:00:00"}