{"id":"https://openalex.org/W6998415211","doi":null,"title":"Adversarial cross-modal unsupervised domain adaptation in semantic segmentation","display_name":"Adversarial cross-modal unsupervised domain adaptation in semantic segmentation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W6998415211"},"language":"en","primary_location":{"id":"pmh:oai:dr.ntu.edu.sg:10356/159248","doi":null,"is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/159248","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis-Master by Coursework"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shi, Mengqi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shi, Mengqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10036","display_name":"Advanced Neural Network Applications","score":9.999999747378752e-05,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0,"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/unsupervised-domain-adaptation","display_name":"unsupervised domain adaptation","score":0.9769999980926514},{"id":"https://openalex.org/keywords/3d-semantic-segmentation","display_name":"3D semantic segmentation","score":0.9629999995231628},{"id":"https://openalex.org/keywords/cross-modal-learning","display_name":"cross-modal learning","score":0.7680000066757202},{"id":"https://openalex.org/keywords/adversarial-machine-learning","display_name":"adversarial learning","score":0.9890000224113464},{"id":"https://openalex.org/keywords/advent","display_name":"Advent","score":0.9900000095367432},{"id":"https://openalex.org/keywords/overfitting","display_name":"overfitting","score":0.9010000228881836},{"id":"https://openalex.org/keywords/autonomous-driving","display_name":"autonomous driving","score":0.7990000247955322}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7983999848365784},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.7688999772071838},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7651000022888184},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7146999835968018},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6883000135421753},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5527999997138977},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5037000179290771},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5019000172615051},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4569999873638153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45339998602867126},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4293000102043152},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.37290000915527344},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.3465000092983246},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.310699999332428},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2842000126838684},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C198942812","wikidata":"https://www.wikidata.org/wiki/Q496618","display_name":"Semantic property","level":2,"score":0.24950000643730164},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.24420000612735748},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.23739999532699585},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.22470000386238098},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.22439999878406525},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.21639999747276306},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.20649999380111694},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.19990000128746033},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.19789999723434448},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.19619999825954437},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.1881999969482422},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.18700000643730164},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1868000030517578},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.17080000042915344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16699999570846558},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.1607999950647354},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.1581999957561493},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.1559000015258789},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.15160000324249268},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.15160000324249268}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:dr.ntu.edu.sg:10356/159248","doi":null,"is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/159248","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis-Master by Coursework"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4315488960","https://openalex.org/W4288009800","https://openalex.org/W4413402787","https://openalex.org/W4388191323","https://openalex.org/W3163179572","https://openalex.org/W3125698590","https://openalex.org/W7131878908","https://openalex.org/W4412871044","https://openalex.org/W7155172104","https://openalex.org/W7160086348"],"abstract_inverted_index":{"3D":[0,39,64,95],"semantic":[1,42,69],"segmentation":[2,43],"is":[3,44,154],"a":[4,12,46,76,122,149,176],"vital":[5],"problem":[6,30],"in":[7,15,41,68,88,170,186,190,197],"automatic":[8],"driving,":[9],"and":[10,56,82,92,96,115,130,167,180,200],"thus":[11],"\\nhot":[13],"field":[14],"deep":[16],"learning.":[17],"These":[18],"days,":[19],"the":[20,29,61,128,146,152,158,163,193,208],"research":[21,37,50,161],"for":[22,27],"unsupervised":[23],"domain":[24],"\\nadaptation":[25],"rises":[26],"solving":[28],"of":[31,63,133,178,192],"lacking":[32],"annotated":[33],"datasets.":[34],"However,":[35,151],"\\nthe":[36],"on":[38,80,106,162],"UDA":[40,65,108],"still":[45,155],"blue":[47],"sea.":[48],"\\nOur":[49],"aims":[51],"to":[52,59],"combine":[53],"adversarial":[54],"learning":[55],"cross-modal":[57,107,143,168,182],"networks":[58],"\\nboost":[60],"performance":[62,135,153],"across":[66],"datasets":[67],"segmentation.":[70],"\\nWith":[71],"this":[72,89,100],"goal,":[73],"we":[74,102,111,139,174,203],"propose":[75],"new":[77],"solution":[78],"based":[79],"xMUDA":[81],"ADVENT,":[83],"\\nresearch":[84],"several":[85],"detailed":[86],"change":[87],"novel":[90],"network":[91],"obtain":[93],"better":[94,156,185],"\\noverall":[97],"performances.":[98],"\\nIn":[99],"dissertation,":[101],"use":[103],"independent":[104],"discriminators":[105,144],"networks.":[109],"\\nFirstly,":[110],"add":[112,140],"uni-modal":[113],"ones":[114],"get":[116],"our":[117,171,201,205],"best":[118],"solution,":[119],"which":[120],"has":[121],"\\n3D":[123],"mIoU":[124],"7.53%":[125],"higher":[126],"than":[127,157],"baseline":[129,199],"an":[131],"improvement":[132],"overall":[134],"\\nby":[136],"3.68%.":[137],"Then,":[138],"two":[141],"more":[142],"but":[145],"\\nperformance":[147],"suffers":[148],"decrease.":[150],"\\nbaseline.":[159],"To":[160],"priority":[164],"between":[165],"MaxSqaureLoss":[166],"\\nloss":[169],"aiming":[172],"task,":[173],"design":[175],"pair":[177],"experiments":[179],"find":[181],"\\nmethod":[183],"act":[184],"such":[187],"tasks.":[188],"\\nFinally,":[189],"terms":[191],"over-fitting":[194],"issue":[195],"occurring":[196],"both":[198],"\\nmethod,":[202],"give":[204],"thoughts":[206],"about":[207],"cause.":[209]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}