{"id":"https://openalex.org/W4408700890","doi":"https://doi.org/10.1109/itsc58415.2024.10920237","title":"ChangeSAM: Adapting the Segment Anything Model to Street Scene Image Change Detection","display_name":"ChangeSAM: Adapting the Segment Anything Model to Street Scene Image Change Detection","publication_year":2024,"publication_date":"2024-09-24","ids":{"openalex":"https://openalex.org/W4408700890","doi":"https://doi.org/10.1109/itsc58415.2024.10920237"},"language":"en","primary_location":{"id":"doi:10.1109/itsc58415.2024.10920237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10920237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)","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/A5015370463","display_name":"Adrian Bauer","orcid":"https://orcid.org/0000-0002-2557-9536"},"institutions":[{"id":"https://openalex.org/I167360494","display_name":"University of Wuppertal","ror":"https://ror.org/00613ak93","country_code":"DE","type":"education","lineage":["https://openalex.org/I167360494"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Adrian Bauer","raw_affiliation_strings":["University of Wuppertal,Germany"],"affiliations":[{"raw_affiliation_string":"University of Wuppertal,Germany","institution_ids":["https://openalex.org/I167360494"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093096993","display_name":"Jan-Christoph Krabbe","orcid":null},"institutions":[{"id":"https://openalex.org/I167360494","display_name":"University of Wuppertal","ror":"https://ror.org/00613ak93","country_code":"DE","type":"education","lineage":["https://openalex.org/I167360494"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jan-Christoph Krabbe","raw_affiliation_strings":["University of Wuppertal,Germany"],"affiliations":[{"raw_affiliation_string":"University of Wuppertal,Germany","institution_ids":["https://openalex.org/I167360494"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080666933","display_name":"Anton Kummert","orcid":"https://orcid.org/0000-0002-0282-5087"},"institutions":[{"id":"https://openalex.org/I167360494","display_name":"University of Wuppertal","ror":"https://ror.org/00613ak93","country_code":"DE","type":"education","lineage":["https://openalex.org/I167360494"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anton Kummert","raw_affiliation_strings":["University of Wuppertal,Germany"],"affiliations":[{"raw_affiliation_string":"University of Wuppertal,Germany","institution_ids":["https://openalex.org/I167360494"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015370463"],"corresponding_institution_ids":["https://openalex.org/I167360494"],"apc_list":null,"apc_paid":null,"fwci":0.3143,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67605862,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1672","last_page":"1677"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9769999980926514,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9598000049591064,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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":0.6618679761886597},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5716108083724976},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5504763722419739},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5429612398147583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48124265670776367},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3685934543609619}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6618679761886597},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5716108083724976},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5504763722419739},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5429612398147583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48124265670776367},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3685934543609619}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc58415.2024.10920237","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc58415.2024.10920237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)","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":21,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W2194775991","https://openalex.org/W2891248708","https://openalex.org/W3010257550","https://openalex.org/W3025573667","https://openalex.org/W3090836511","https://openalex.org/W3094171276","https://openalex.org/W3096808073","https://openalex.org/W3176659256","https://openalex.org/W3210193870","https://openalex.org/W4205991051","https://openalex.org/W4319457815","https://openalex.org/W4382322597","https://openalex.org/W4390190100","https://openalex.org/W4390874575","https://openalex.org/W4391991763","https://openalex.org/W4408634392","https://openalex.org/W6637373629","https://openalex.org/W6796581206","https://openalex.org/W6854362512"],"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],"the":[1,40,62,123,145,155],"dynamic":[2],"field":[3],"of":[4,51,67,148,159],"machine":[5],"learning,":[6],"foundation":[7,149],"models":[8,150,162],"have":[9],"recently":[10],"gained":[11],"prominence,":[12],"particularly":[13],"for":[14,31,42,53],"their":[15],"application":[16],"in":[17,76,151,163],"natural":[18],"language":[19],"processing":[20],"and":[21,64,89,105,118,157],"computer":[22],"vision.":[23],"The":[24],"foundational":[25],"Segment":[26],"Anything":[27],"Model":[28],"(SAM),":[29],"known":[30],"its":[32],"interactive":[33],"image":[34,56,77],"segmentation":[35],"via":[36],"prompts,":[37],"serves":[38],"as":[39,170],"basis":[41],"this":[43],"study.":[44],"We":[45],"introduce":[46],"ChangeSAM,":[47],"a":[48,112],"tailored":[49],"adaptation":[50],"SAM":[52],"street":[54],"scene":[55],"change":[57],"detection":[58],"(CD).":[59],"ChangeSAM":[60,96,132],"utilizes":[61],"versatility":[63],"vast":[65],"knowledge":[66],"SAM,":[68],"adapting":[69],"it":[70],"to":[71,97,144],"effectively":[72],"identify":[73],"semantic":[74],"changes":[75],"pairs.":[78],"Two":[79],"architectural":[80],"adaptations":[81],"are":[82,109],"introduced":[83],"-":[84,94],"Pre":[85],"Decoder":[86,91],"Fusion":[87,92],"(PreDF)":[88],"Post":[90],"(PostDF)":[93],"enabling":[95],"process":[98],"dual":[99],"images.":[100],"Enhancements":[101],"through":[102],"Prompt":[103],"Tuning":[104],"Low-Rank":[106],"Adaptation":[107],"(LoRA)":[108],"integrated,":[110],"achieving":[111],"balance":[113],"between":[114],"reusability,":[115],"computational":[116,167],"efficiency,":[117],"accuracy.":[119],"Our":[120],"evaluation":[121],"on":[122,135],"VL-CMU-CD":[124],"dataset":[125],"shows":[126],"that":[127],"with":[128,137,165],"minimal":[129],"parameter":[130],"adjustments,":[131],"achieves":[133],"accuracy":[134],"par":[136],"fully":[138],"fine-tuned":[139],"models.":[140],"This":[141],"work":[142],"contributes":[143],"ongoing":[146],"development":[147],"practical":[152],"applications,":[153],"illustrating":[154],"viability":[156],"potential":[158],"adaptable,":[160],"efficient":[161],"scenarios":[164],"limited":[166],"resources,":[168],"such":[169],"intelligent":[171],"vehicles.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
