{"id":"https://openalex.org/W4408352411","doi":"https://doi.org/10.1109/icassp49660.2025.10888537","title":"Diffusion Features to Bridge Domain Gap for Semantic Segmentation","display_name":"Diffusion Features to Bridge Domain Gap for Semantic Segmentation","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408352411","doi":"https://doi.org/10.1109/icassp49660.2025.10888537"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10888537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888537","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5075606969","display_name":"Yuxiang Ji","orcid":"https://orcid.org/0009-0005-8802-7535"},"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":"Yuxiang Ji","raw_affiliation_strings":["Xiamen University,Institute of Artifcial Intelligence,Xiamen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen University,Institute of Artifcial Intelligence,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033686089","display_name":"Boyong He","orcid":"https://orcid.org/0000-0002-9047-866X"},"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":"Boyong He","raw_affiliation_strings":["Xiamen University,Institute of Artifcial Intelligence,Xiamen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen University,Institute of Artifcial Intelligence,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102967598","display_name":"Chenyuan Qu","orcid":"https://orcid.org/0009-0000-4814-2022"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chenyuan Qu","raw_affiliation_strings":["University of Birmingham,School of Computer Science,Birmingham,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Birmingham,School of Computer Science,Birmingham,United Kingdom","institution_ids":["https://openalex.org/I79619799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113133173","display_name":"Zhuoyue Tan","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":"Zhuoyue Tan","raw_affiliation_strings":["Xiamen University,Institute of Artifcial Intelligence,Xiamen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen University,Institute of Artifcial Intelligence,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072469414","display_name":"Chuan Qin","orcid":"https://orcid.org/0000-0002-0370-4623"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chuan Qin","raw_affiliation_strings":["The University of Melbourne,Department of Infrastructure Engineering,Melbourne,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Melbourne,Department of Infrastructure Engineering,Melbourne,Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048639585","display_name":"Liaoni Wu","orcid":"https://orcid.org/0000-0002-4558-0462"},"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":"Liaoni Wu","raw_affiliation_strings":["Xiamen University,Institute of Artifcial Intelligence,Xiamen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen University,Institute of Artifcial Intelligence,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.0351,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.96246595,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.6269000172615051,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.6269000172615051,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6962721943855286},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.6557890772819519},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5730928778648376},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5455231070518494},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4787242114543915},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.4581218957901001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4078390896320343},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0761120617389679},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07028442621231079},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06795650720596313},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.066243976354599}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6962721943855286},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.6557890772819519},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5730928778648376},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5455231070518494},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4787242114543915},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.4581218957901001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4078390896320343},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0761120617389679},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07028442621231079},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06795650720596313},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.066243976354599},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10888537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888537","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2431874326","https://openalex.org/W2487365028","https://openalex.org/W2781228439","https://openalex.org/W2884366600","https://openalex.org/W3000172657","https://openalex.org/W3035564946","https://openalex.org/W3133542152","https://openalex.org/W3138516171","https://openalex.org/W3175215201","https://openalex.org/W3175217175","https://openalex.org/W3180439858","https://openalex.org/W3207649350","https://openalex.org/W3211490618","https://openalex.org/W3217147624","https://openalex.org/W4289639938","https://openalex.org/W4312719508","https://openalex.org/W4312933868","https://openalex.org/W4386075819","https://openalex.org/W4390190321","https://openalex.org/W4390873429","https://openalex.org/W4393150367","https://openalex.org/W6639480849","https://openalex.org/W6784333009","https://openalex.org/W6805547681","https://openalex.org/W6849938875","https://openalex.org/W6853281718","https://openalex.org/W6853559265","https://openalex.org/W6853660567","https://openalex.org/W6854453267","https://openalex.org/W6861057767"],"related_works":["https://openalex.org/W1501776718","https://openalex.org/W2615136228","https://openalex.org/W657108774","https://openalex.org/W2390192952","https://openalex.org/W2480620430","https://openalex.org/W2565795945","https://openalex.org/W2373296418","https://openalex.org/W4239538403","https://openalex.org/W1515761309","https://openalex.org/W4301400761"],"abstract_inverted_index":{"Pre-trained":[0],"diffusion":[1,42,68,90],"models":[2,43,69],"have":[3],"demonstrated":[4],"remarkable":[5],"proficiency":[6],"in":[7,47,117,133],"synthesizing":[8],"images":[9],"across":[10,136],"a":[11,78,102],"wide":[12],"range":[13],"of":[14,36,67,96,120],"scenarios":[15],"with":[16],"customizable":[17],"prompts,":[18],"indicating":[19],"their":[20],"effective":[21,85],"capacity":[22],"to":[23,44,63,107],"capture":[24],"universal":[25],"features.":[26],"Motivated":[27],"by":[28],"this,":[29],"our":[30,128],"study":[31],"delves":[32],"into":[33],"the":[34,37,54,58,65,89,94,118,141],"utilization":[35],"implicit":[38],"knowledge":[39,111],"embedded":[40],"within":[41],"address":[45],"challenges":[46],"cross-domain":[48],"semantic":[49,86,123],"segmentation.":[50],"This":[51],"paper":[52],"investigates":[53],"approach":[55],"that":[56,127],"leverages":[57],"sampling":[59],"and":[60,83,139],"fusion":[61],"techniques":[62],"harness":[64],"features":[66],"efficiently.":[70],"We":[71],"propose":[72],"DIffusion":[73],"Feature":[74],"Fusion":[75],"(DIFF)":[76],"as":[77],"backbone":[79],"use":[80],"for":[81],"extracting":[82],"integrating":[84],"representations":[87],"through":[88],"process.":[91],"By":[92],"leveraging":[93],"strength":[95],"text-to-image":[97],"generation":[98],"capability,":[99],"we":[100,125],"introduce":[101],"new":[103],"training":[104],"framework":[105],"designed":[106],"implicitly":[108],"learn":[109],"posterior":[110],"from":[112],"it.":[113],"Through":[114],"rigorous":[115],"evaluation":[116],"contexts":[119],"domain":[121],"generalization":[122],"segmentation,":[124],"establish":[126],"methodology":[129],"surpasses":[130],"preceding":[131],"approaches":[132],"mitigating":[134],"discrepancies":[135],"distinct":[137],"domains":[138],"attains":[140],"state-of-the-art":[142],"(SOTA)":[143],"benchmark.":[144],"The":[145],"implementation":[146],"code":[147],"is":[148],"released":[149],"at":[150],"https://github.com/Yux1angJi/DIFF.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}