{"id":"https://openalex.org/W4413146656","doi":"https://doi.org/10.1109/cvpr52734.2025.00966","title":"DiffCAM: Data-Driven Saliency Maps by Capturing Feature Differences","display_name":"DiffCAM: Data-Driven Saliency Maps by Capturing Feature Differences","publication_year":2025,"publication_date":"2025-06-10","ids":{"openalex":"https://openalex.org/W4413146656","doi":"https://doi.org/10.1109/cvpr52734.2025.00966"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52734.2025.00966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52734.2025.00966","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5100770663","display_name":"Xingjian Li","orcid":"https://orcid.org/0000-0001-8073-7552"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingjian Li","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,United States,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,United States,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018113033","display_name":"Qiming Zhao","orcid":"https://orcid.org/0000-0002-9754-0067"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiming Zhao","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,United States,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,United States,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047758978","display_name":"Neha Bisht","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neelesh Bisht","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,United States,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,United States,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108936928","display_name":"Mostofa Rafid Uddin","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mostofa Rafid Uddin","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,United States,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,United States,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010761233","display_name":"J. Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin Yu Kim","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,United States,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,United States,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005337426","display_name":"Bryan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan Zhang","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,United States,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,United States,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000807861","display_name":"Min Xu","orcid":"https://orcid.org/0000-0002-0881-5891"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Min Xu","raw_affiliation_strings":["Carnegie Mellon University,Pittsburgh,PA,United States,15213"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Pittsburgh,PA,United States,15213","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10327","last_page":"10337"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9965000152587891,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9965000152587891,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9315999746322632,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9013000130653381,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.6949566602706909},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6126498579978943},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49964427947998047},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.45109012722969055},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44436368346214294},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.3640422523021698}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6949566602706909},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6126498579978943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49964427947998047},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.45109012722969055},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44436368346214294},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3640422523021698},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52734.2025.00966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52734.2025.00966","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.800000011920929,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W2013728941","https://openalex.org/W4225274103","https://openalex.org/W2154046714","https://openalex.org/W2189613078","https://openalex.org/W2579659702","https://openalex.org/W2923661510","https://openalex.org/W1574055964","https://openalex.org/W1965329638"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"the":[3,31,54,95,100,119,148],"interpretability":[4],"of":[5,33,57,99,138,153],"Deep":[6],"Neural":[7],"Networks":[8],"(DNNs)":[9],"has":[10],"garnered":[11],"significant":[12],"attention,":[13],"particularly":[14],"due":[15],"to":[16,50,69,86,134],"their":[17],"widespread":[18],"deployment":[19],"in":[20,72,155],"critical":[21],"domains":[22],"like":[23],"healthcare,":[24],"finance,":[25],"and":[26,151,162],"autonomous":[27],"systems.":[28],"To":[29],"address":[30],"challenge":[32],"understanding":[34],"how":[35,108],"DNNs":[36],"make":[37],"decisions,":[38],"Explainable":[39],"AI":[40],"(XAI)":[41],"methods,":[42],"such":[43],"as":[44],"saliency":[45],"maps,":[46],"have":[47],"been":[48],"developed":[49],"provide":[51],"insights":[52],"into":[53],"inner":[55],"workings":[56],"these":[58],"models.":[59,142],"This":[60,116],"paper":[61],"introduces":[62],"DiffCAM,":[63],"a":[64,109,135],"novel":[65],"XAI":[66],"method":[67],"designed":[68],"overcome":[70],"limitations":[71],"existing":[73],"Class":[74],"Activation":[75],"Map":[76],"(CAM)-based":[77],"techniques,":[78],"which":[79],"often":[80],"rely":[81],"on":[82,107,125],"decision":[83,126],"boundary":[84],"gradients":[85],"estimate":[87],"feature":[88,104],"importance.":[89],"DiffCAM":[90,132,154],"differentiates":[91],"itself":[92],"by":[93],"considering":[94],"actual":[96],"data":[97],"distribution":[98],"reference":[101,114],"class,":[102],"identifying":[103],"importance":[105],"based":[106],"target":[110],"example":[111],"differs":[112],"from":[113],"examples.":[115],"approach":[117],"captures":[118],"most":[120],"discriminative":[121],"features":[122],"without":[123],"relying":[124],"boundaries":[127],"or":[128],"prediction":[129],"results,":[130],"making":[131],"applicable":[133],"broader":[136],"range":[137],"models,":[139],"including":[140],"foundation":[141],"Through":[143],"extensive":[144],"experiments,":[145],"we":[146],"demonstrate":[147],"superior":[149],"performance":[150],"flexibility":[152],"providing":[156],"meaningful":[157],"explanations":[158],"across":[159],"diverse":[160],"datasets":[161],"scenarios.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}