{"id":"https://openalex.org/W7164814401","doi":"https://doi.org/10.1145/3805622.3810707","title":"HD\u00b2FI-Net: Hierarchical Dual-Domain Fusion\u2013Interaction Network for RGB-T Semantic Segmentation","display_name":"HD\u00b2FI-Net: Hierarchical Dual-Domain Fusion\u2013Interaction Network for RGB-T Semantic Segmentation","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164814401","doi":"https://doi.org/10.1145/3805622.3810707"},"language":null,"primary_location":{"id":"doi:10.1145/3805622.3810707","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810707","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805622.3810707","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138679713","display_name":"Zhenrong Guo","orcid":"https://orcid.org/0009-0006-3488-2787"},"institutions":[{"id":"https://openalex.org/I176808543","display_name":"Liaoning Technical University","ror":"https://ror.org/01n2bd587","country_code":"CN","type":"education","lineage":["https://openalex.org/I176808543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenrong Guo","raw_affiliation_strings":["Liaoning Technical University, Huludao, China"],"raw_orcid":"https://orcid.org/0009-0006-3488-2787","affiliations":[{"raw_affiliation_string":"Liaoning Technical University, Huludao, China","institution_ids":["https://openalex.org/I176808543"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046241939","display_name":"Bowen Fei","orcid":"https://orcid.org/0000-0001-6635-0538"},"institutions":[{"id":"https://openalex.org/I176808543","display_name":"Liaoning Technical University","ror":"https://ror.org/01n2bd587","country_code":"CN","type":"education","lineage":["https://openalex.org/I176808543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Fei","raw_affiliation_strings":["Liaoning Technical University, Huludao, China"],"raw_orcid":"https://orcid.org/0000-0001-6635-0538","affiliations":[{"raw_affiliation_string":"Liaoning Technical University, Huludao, China","institution_ids":["https://openalex.org/I176808543"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047055086","display_name":"Daqian Liu","orcid":"https://orcid.org/0000-0002-7583-9578"},"institutions":[{"id":"https://openalex.org/I176808543","display_name":"Liaoning Technical University","ror":"https://ror.org/01n2bd587","country_code":"CN","type":"education","lineage":["https://openalex.org/I176808543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daqian Liu","raw_affiliation_strings":["Liaoning Technical University, Huludao, China"],"raw_orcid":"https://orcid.org/0000-0002-7583-9578","affiliations":[{"raw_affiliation_string":"Liaoning Technical University, Huludao, China","institution_ids":["https://openalex.org/I176808543"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138669901","display_name":"Jiahao Zhang","orcid":"https://orcid.org/0009-0002-0831-8737"},"institutions":[{"id":"https://openalex.org/I176808543","display_name":"Liaoning Technical University","ror":"https://ror.org/01n2bd587","country_code":"CN","type":"education","lineage":["https://openalex.org/I176808543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahao Zhang","raw_affiliation_strings":["Liaoning Technical University, Huludao, China"],"raw_orcid":"https://orcid.org/0009-0002-0831-8737","affiliations":[{"raw_affiliation_string":"Liaoning Technical University, Huludao, China","institution_ids":["https://openalex.org/I176808543"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.93457166,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1385","last_page":"1393"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.8637999892234802,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.8637999892234802,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.02319999970495701,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.01810000091791153,"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/segmentation","display_name":"Segmentation","score":0.6819000244140625},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4722000062465668},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.42989999055862427},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4212000072002411},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4156000018119812},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.39469999074935913},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.38760000467300415},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.3774999976158142},{"id":"https://openalex.org/keywords/crossmodal","display_name":"Crossmodal","score":0.36899998784065247}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.741100013256073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7204999923706055},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6819000244140625},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4722000062465668},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.42989999055862427},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.3774999976158142},{"id":"https://openalex.org/C60115397","wikidata":"https://www.wikidata.org/wiki/Q5188732","display_name":"Crossmodal","level":4,"score":0.36899998784065247},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.35899999737739563},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3587000072002411},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3149999976158142},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.30959999561309814},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C193125573","wikidata":"https://www.wikidata.org/wiki/Q7449065","display_name":"Semantic interpretation","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2872999906539917},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.26829999685287476},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2680000066757202},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805622.3810707","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810707","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805622.3810707","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810707","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W2774839435","https://openalex.org/W2921749009","https://openalex.org/W2971014764","https://openalex.org/W3046194589","https://openalex.org/W3091001089","https://openalex.org/W3091791645","https://openalex.org/W3166016280","https://openalex.org/W3198062544","https://openalex.org/W4224111766","https://openalex.org/W4286565909","https://openalex.org/W4292828877","https://openalex.org/W4296913506","https://openalex.org/W4298326888","https://openalex.org/W4311766828","https://openalex.org/W4312402232","https://openalex.org/W4312594135","https://openalex.org/W4313139043","https://openalex.org/W4313639507","https://openalex.org/W4319879001","https://openalex.org/W4376464632","https://openalex.org/W4381300351","https://openalex.org/W4383336674","https://openalex.org/W4385488625","https://openalex.org/W4386179772","https://openalex.org/W4386275800","https://openalex.org/W4390489106","https://openalex.org/W4390590999","https://openalex.org/W4390873110","https://openalex.org/W4392343478","https://openalex.org/W4402753319","https://openalex.org/W4403722461","https://openalex.org/W4408100010","https://openalex.org/W4411402750","https://openalex.org/W4416308820"],"related_works":[],"abstract_inverted_index":{"Robust":[0],"perception":[1],"under":[2],"adverse":[3],"illumination":[4],"demands":[5],"fusing":[6],"complementary":[7,60],"RGB":[8],"and":[9,55,83,118,140,156],"thermal":[10],"cues":[11],"for":[12,32,97,105],"dense":[13],"scene":[14,34],"understanding.":[15],"The":[16],"core":[17],"challenge":[18],"of":[19,59],"RGB-Thermal":[20],"semantic":[21,151],"segmentation":[22,152],"lies":[23],"in":[24,149],"reconciling":[25],"modality":[26],"heterogeneity":[27],"while":[28],"exploiting":[29],"multi-level":[30],"complementarity":[31],"robust":[33],"parsing.":[35],"Existing":[36],"methods":[37,148],"commonly":[38],"adopt":[39],"single-domain":[40],"alignment":[41],"or":[42],"hierarchy-agnostic":[43],"fusion":[44,89,107,114],"to":[45,125],"establish":[46],"cross-modal":[47,78,103],"features.":[48],"However,":[49],"these":[50,64],"approaches":[51],"neglect":[52],"frequency\u2013spatial":[53],"consistency":[54,79],"the":[56,122,135],"hierarchy-specific":[57],"nature":[58],"information.":[61],"To":[62],"address":[63],"limitations,":[65],"we":[66],"propose":[67],"HD2FI-Net,":[68],"a":[69],"Hierarchical":[70],"Dual-Domain":[71],"Fusion\u2013Interaction":[72],"Network.":[73],"Geo-semantic":[74],"coupled":[75],"rectification":[76],"enforces":[77],"via":[80],"direction-aware":[81],"attention":[82,104,117],"bidirectional":[84],"residual":[85],"rectification.":[86],"Unified":[87],"dual-domain":[88,98],"&":[90],"interaction":[91],"first":[92],"performs":[93],"shared":[94],"frequency":[95],"modulation":[96],"alignment,":[99],"then":[100],"employs":[101,115],"hybrid":[102],"fine-grained":[106],"at":[108,121],"deep":[109],"stages.":[110],"Contrastive":[111],"boundary":[112,127],"difference":[113],"parameter-free":[116],"differential":[119],"modeling":[120],"shallowest":[123],"stage":[124],"preserve":[126],"details":[128],"with":[129,153],"minimal":[130],"overhead.":[131],"Extensive":[132],"experiments":[133],"on":[134],"benchmark":[136],"datasets":[137],"MFNet,":[138],"PST900,":[139],"FMB":[141],"demonstrate":[142],"that":[143],"HD2FI-Net":[144],"outperforms":[145],"several":[146],"state-of-the-art":[147],"RGB-T":[150],"superior":[154],"performance":[155],"lightweight":[157],"efficiency.":[158]},"counts_by_year":[],"updated_date":"2026-06-16T07:37:23.134862","created_date":"2026-06-16T00:00:00"}