{"id":"https://openalex.org/W4409659935","doi":"https://doi.org/10.1109/icit63637.2025.10965269","title":"Multi-Level Features Fusion for Zero-Shot Object Pose Estimation","display_name":"Multi-Level Features Fusion for Zero-Shot Object Pose Estimation","publication_year":2025,"publication_date":"2025-03-26","ids":{"openalex":"https://openalex.org/W4409659935","doi":"https://doi.org/10.1109/icit63637.2025.10965269"},"language":"en","primary_location":{"id":"doi:10.1109/icit63637.2025.10965269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit63637.2025.10965269","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 Industrial Technology (ICIT)","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/A5049369402","display_name":"Nanxin Huang","orcid":"https://orcid.org/0000-0002-4145-6202"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nanxin Huang","raw_affiliation_strings":["School of Automation, China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education,Wuhan,China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020134430","display_name":"Chi Xu","orcid":"https://orcid.org/0000-0001-6036-5763"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chi Xu","raw_affiliation_strings":["School of Automation, China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education,Wuhan,China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9858999848365784,"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":0.9858999848365784,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.947700023651123,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T14510","display_name":"Medical Imaging and Analysis","score":0.9361000061035156,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/computer-science","display_name":"Computer science","score":0.6605618596076965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6196466088294983},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6113384366035461},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5804444551467896},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5512915849685669},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5495669841766357},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.5095822811126709},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.49052828550338745},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4576933979988098},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32636284828186035}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6605618596076965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6196466088294983},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6113384366035461},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5804444551467896},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5512915849685669},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5495669841766357},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.5095822811126709},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.49052828550338745},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4576933979988098},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32636284828186035},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icit63637.2025.10965269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit63637.2025.10965269","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 Industrial Technology (ICIT)","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":33,"referenced_works":["https://openalex.org/W132147841","https://openalex.org/W1909903157","https://openalex.org/W2963177347","https://openalex.org/W2963756608","https://openalex.org/W2981378444","https://openalex.org/W2986303149","https://openalex.org/W3009516594","https://openalex.org/W3034712732","https://openalex.org/W3034986117","https://openalex.org/W3107992529","https://openalex.org/W3177069133","https://openalex.org/W3201312429","https://openalex.org/W4221167997","https://openalex.org/W4225435562","https://openalex.org/W4281557677","https://openalex.org/W4298014068","https://openalex.org/W4312364980","https://openalex.org/W4313134354","https://openalex.org/W4321033239","https://openalex.org/W4386075525","https://openalex.org/W4386075656","https://openalex.org/W4386075917","https://openalex.org/W4390873470","https://openalex.org/W4390874431","https://openalex.org/W4394825402","https://openalex.org/W4399566672","https://openalex.org/W4401417458","https://openalex.org/W4402713109","https://openalex.org/W4402727436","https://openalex.org/W4402727742","https://openalex.org/W4402753846","https://openalex.org/W4402754209","https://openalex.org/W6857185434"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2152662039"],"abstract_inverted_index":{"Driven":[0],"by":[1,77,122],"advancements":[2],"in":[3,17,98],"industrial":[4],"production":[5],"and":[6,22,72,135,139,165],"artificial":[7],"intelligence,":[8],"the":[9,37,43,47,78,93,99,132,145],"need":[10],"for":[11,49],"pose":[12,32],"estimation":[13,33],"of":[14,39,114],"new":[15],"ob-jects":[16],"areas":[18],"like":[19],"robotic":[20],"manipulation":[21],"virtual":[23],"reality":[24],"is":[25,53],"increasing.":[26],"We":[27],"introduce":[28],"a":[29,56,66,87,105],"zero-shot":[30],"object":[31],"approach":[34,155],"that":[35,153,168],"identifies":[36],"poses":[38],"objects":[40,128],"excluded":[41],"from":[42,131],"training":[44,133],"dataset,":[45],"removing":[46],"requirement":[48],"re-modeling.":[50],"The":[51],"method":[52,118,170],"built":[54],"around":[55],"multi-level":[57,74,115],"features":[58,75],"fusion":[59,101,113],"framework":[60],"de-signed":[61],"to":[62,91,110,143],"enhance":[63,92],"generalization.":[64],"First,":[65],"trainable":[67],"feature":[68,94,100,141],"extraction":[69,95],"module":[70],"filters":[71],"selects":[73],"extracted":[76],"backbone":[79],"network.":[80],"Unlike":[81],"traditional":[82],"convolutional":[83],"ker-nels,":[84],"we":[85,103],"incorporate":[86],"dynamic":[88,106],"convolution":[89],"kernel":[90],"capability.":[96],"Second,":[97],"module,":[102],"adopt":[104],"weight":[107],"generation":[108],"strategy":[109],"perform":[111],"weighted":[112],"features.":[116],"This":[117],"enhances":[119],"template":[120],"matching":[121],"effectively":[123],"describing":[124],"similarities":[125],"between":[126],"unseen":[127],"(those":[129],"absent":[130],"set)":[134],"templates,":[136],"leveraging":[137],"robust":[138],"adaptive":[140],"representations":[142],"narrow":[144],"gap":[146],"with":[147],"seen":[148],"objects.":[149],"Experimental":[150],"results":[151],"demonstrate":[152],"our":[154,169],"achieves":[156],"state-of-the-art":[157],"performance":[158],"on":[159],"two":[160],"popu-lar":[161],"benchmark":[162],"datasets,":[163],"LineMod":[164],"LineMod-Occlusion,":[166],"proves":[167],"has":[171],"better":[172],"generalization":[173],"than":[174],"previous":[175],"models.":[176]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
