{"id":"https://openalex.org/W4414085983","doi":"https://doi.org/10.1109/icmew68306.2025.11152142","title":"A Twin-network Architecture for RGB-based Panoramic Semantic Segmentation","display_name":"A Twin-network Architecture for RGB-based Panoramic Semantic Segmentation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4414085983","doi":"https://doi.org/10.1109/icmew68306.2025.11152142"},"language":"en","primary_location":{"id":"doi:10.1109/icmew68306.2025.11152142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew68306.2025.11152142","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 Workshops (ICMEW)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5023467988","display_name":"Jingguo Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingguo Liu","raw_affiliation_strings":["Southwest University,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090565523","display_name":"Jiayao Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayao Liu","raw_affiliation_strings":["Southwest University,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100373826","display_name":"Yujie Wang","orcid":"https://orcid.org/0000-0002-3119-3066"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Wang","raw_affiliation_strings":["Southwest University,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088172355","display_name":"Shigang Li","orcid":"https://orcid.org/0000-0003-0022-7865"},"institutions":[{"id":"https://openalex.org/I57930482","display_name":"Hiroshima City University","ror":"https://ror.org/001et4e78","country_code":"JP","type":"education","lineage":["https://openalex.org/I57930482"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigang Li","raw_affiliation_strings":["Hiroshima City University,Hiroshima,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hiroshima City University,Hiroshima,Japan","institution_ids":["https://openalex.org/I57930482"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100462004","display_name":"Jianfeng Li","orcid":"https://orcid.org/0009-0002-1731-4762"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Li","raw_affiliation_strings":["Southwest University,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":2,"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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":0.9993000030517578,"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":0.9993000030517578,"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/segmentation","display_name":"Segmentation","score":0.703000009059906},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6129999756813049},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5260000228881836},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5066999793052673},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3955000042915344},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.362199991941452},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.35740000009536743}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7919999957084656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7705000042915344},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7699000239372253},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.703000009059906},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6129999756813049},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5260000228881836},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5066999793052673},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3955000042915344},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.35740000009536743},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3343999981880188},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew68306.2025.11152142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew68306.2025.11152142","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 Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2805395174","https://openalex.org/W2963052201","https://openalex.org/W2963591054","https://openalex.org/W2963896186","https://openalex.org/W2969261403","https://openalex.org/W2979485822","https://openalex.org/W2984128514","https://openalex.org/W3015871565","https://openalex.org/W3034515714","https://openalex.org/W3108601100","https://openalex.org/W3109728105","https://openalex.org/W3110108516","https://openalex.org/W3124434019","https://openalex.org/W3175201472","https://openalex.org/W3194841206","https://openalex.org/W3202422321","https://openalex.org/W3207537403","https://openalex.org/W3208869643","https://openalex.org/W4221142197","https://openalex.org/W4229723800","https://openalex.org/W4313169545","https://openalex.org/W4319300281","https://openalex.org/W4385764506","https://openalex.org/W4386076408","https://openalex.org/W4394593124","https://openalex.org/W4394597661"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"In":[0,30],"panoramic":[1,103,119,143],"semantic":[2,18,80,85],"segmentation":[3,92],"field,":[4],"increasing":[5],"studies":[6],"have":[7],"focused":[8],"on":[9,111,138],"the":[10,15,60,73,78,89,131],"RGB-D":[11],"input,":[12,50],"to":[13,63,99],"enhance":[14],"precision":[16],"of":[17,91,134],"segmentation.":[19],"However,":[20],"acquiring":[21],"depth":[22,53,61,65,75,83],"information":[23,54],"in":[24,102,118],"real-world":[25],"applications":[26],"remains":[27],"a":[28,35,40,97],"challenge.":[29],"this":[31],"paper,":[32],"we":[33,58,71,95,114],"propose":[34,96],"novel":[36],"twin-network":[37],"architecture":[38],"with":[39,77],"two-stage":[41],"training":[42],"approach.":[43],"our":[44,135],"proposed":[45,136],"method":[46,137],"only":[47],"requires":[48],"RGB":[49,68],"but":[51],"incorporates":[52],"within":[55],"it.":[56],"First,":[57],"train":[59],"branch":[62],"extract":[64],"cues":[66],"from":[67],"images.":[69,104],"Then,":[70],"concatenate":[72],"latent":[74],"features":[76],"high-level":[79],"features,":[81],"aligning":[82],"and":[84,124],"information,":[86],"serving":[87],"as":[88],"input":[90],"decoder.":[93],"Furthermore,":[94],"technique":[98],"address":[100],"distortion":[101],"By":[105],"embedding":[106],"Deformable":[107],"Multilayer":[108],"Perceptron(DMLP)":[109],"modules":[110],"skip":[112],"connections,":[113],"effectively":[115],"eliminate":[116],"distortions":[117],"images":[120],"while":[121],"fusing":[122],"local":[123],"global":[125],"image":[126],"characteristics.":[127],"Experimental":[128],"results":[129],"validate":[130],"exceptional":[132],"performance":[133],"two":[139],"widely":[140],"used":[141],"indoor":[142],"datasets.":[144]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}