{"id":"https://openalex.org/W3215142194","doi":"https://doi.org/10.1109/tnnls.2021.3130168","title":"Image Manipulation Localization Using Attentional Cross-Domain CNN Features","display_name":"Image Manipulation Localization Using Attentional Cross-Domain CNN Features","publication_year":2021,"publication_date":"2021-12-02","ids":{"openalex":"https://openalex.org/W3215142194","doi":"https://doi.org/10.1109/tnnls.2021.3130168","mag":"3215142194","pmid":"https://pubmed.ncbi.nlm.nih.gov/34855602"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3130168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3130168","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shuaibo Li","orcid":"https://orcid.org/0000-0001-8542-4168"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuaibo Li","raw_affiliation_strings":["Faculty of Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8542-4168","affiliations":[{"raw_affiliation_string":"Faculty of Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shibiao Xu","orcid":"https://orcid.org/0000-0003-4037-9900"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shibiao Xu","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4037-9900","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Ma","orcid":"https://orcid.org/0000-0001-9652-4260"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Ma","raw_affiliation_strings":["Faculty of Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9652-4260","affiliations":[{"raw_affiliation_string":"Faculty of Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":null,"display_name":"Qiu Zong","orcid":"https://orcid.org/0000-0002-4371-3903"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiu Zong","raw_affiliation_strings":["Faculty of Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4371-3903","affiliations":[{"raw_affiliation_string":"Faculty of Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7901,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.87336665,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"34","issue":"9","first_page":"5614","last_page":"5628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9652000069618225,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9652000069618225,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.008100000210106373,"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.007899999618530273,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/discriminative-model","display_name":"Discriminative model","score":0.8550999760627747},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6335999965667725},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5504000186920166},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5397999882698059},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46880000829696655},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4133000075817108},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4081000089645386},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.39959999918937683},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.34540000557899475}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8550999760627747},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8051999807357788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.775600016117096},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6335999965667725},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5504000186920166},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5397999882698059},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46880000829696655},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46050000190734863},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4081000089645386},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39959999918937683},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.33959999680519104},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.31049999594688416},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3070000112056732},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2928999960422516},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2703000009059906},{"id":"https://openalex.org/C2987933465","wikidata":"https://www.wikidata.org/wiki/Q141130","display_name":"Image manipulation","level":3,"score":0.2606000006198883},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3130168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3130168","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34855602","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34855602","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G351601984","display_name":null,"funder_award_id":"KZ201910005008","funder_id":"https://openalex.org/F4320321793","funder_display_name":"Beijing Municipal Education Commission"},{"id":"https://openalex.org/G3540035971","display_name":null,"funder_award_id":"61771026","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6369404604","display_name":null,"funder_award_id":"61971418","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7466005810","display_name":null,"funder_award_id":"62176010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8030430803","display_name":null,"funder_award_id":"61620106003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321793","display_name":"Beijing Municipal Education Commission","ror":"https://ror.org/04bpn6s66"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W1586939924","https://openalex.org/W1689909837","https://openalex.org/W1982445504","https://openalex.org/W1985729543","https://openalex.org/W2001788007","https://openalex.org/W2009130368","https://openalex.org/W2019370496","https://openalex.org/W2037801532","https://openalex.org/W2049771774","https://openalex.org/W2068734928","https://openalex.org/W2070484489","https://openalex.org/W2071794886","https://openalex.org/W2087361987","https://openalex.org/W2095613088","https://openalex.org/W2097506049","https://openalex.org/W2100495367","https://openalex.org/W2104657103","https://openalex.org/W2108598243","https://openalex.org/W2112789121","https://openalex.org/W2130225759","https://openalex.org/W2162156567","https://openalex.org/W2164990255","https://openalex.org/W2169439181","https://openalex.org/W2179488730","https://openalex.org/W2194775991","https://openalex.org/W2221625691","https://openalex.org/W2328317224","https://openalex.org/W2407561938","https://openalex.org/W2412509443","https://openalex.org/W2515389788","https://openalex.org/W2518397542","https://openalex.org/W2541922885","https://openalex.org/W2554320282","https://openalex.org/W2572561073","https://openalex.org/W2603123944","https://openalex.org/W2605252717","https://openalex.org/W2737725206","https://openalex.org/W2747268660","https://openalex.org/W2752015292","https://openalex.org/W2752782242","https://openalex.org/W2777769595","https://openalex.org/W2884367402","https://openalex.org/W2911605501","https://openalex.org/W2948407537","https://openalex.org/W2963495494","https://openalex.org/W2963678090","https://openalex.org/W2963777235","https://openalex.org/W2963954913","https://openalex.org/W2964146055","https://openalex.org/W3015516611","https://openalex.org/W3082623289","https://openalex.org/W3118971208","https://openalex.org/W3174656926","https://openalex.org/W6620707391","https://openalex.org/W6629148547","https://openalex.org/W6630875275","https://openalex.org/W6637242042","https://openalex.org/W6639102338","https://openalex.org/W6639824700","https://openalex.org/W6640376812","https://openalex.org/W6656557111","https://openalex.org/W6679040668","https://openalex.org/W6685520387","https://openalex.org/W6704241340","https://openalex.org/W6739520758","https://openalex.org/W6740495186","https://openalex.org/W6764782982","https://openalex.org/W6786694419","https://openalex.org/W6788696190","https://openalex.org/W6790623415"],"related_works":[],"abstract_inverted_index":{"Along":[0],"with":[1,86,152],"the":[2,17,90,153,159,163,169,194,203,213,219],"advancement":[3],"of":[4,40,51,105,126,162,180,215],"manipulation":[5],"technologies,":[6],"image":[7,19],"modification":[8],"is":[9,38],"becoming":[10],"increasingly":[11],"convenient":[12],"and":[13,57,63,68,97,116,132,185,201,218],"imperceptible.":[14],"To":[15,166],"tackle":[16],"challenging":[18],"tampering":[20,137],"detection":[21],"problem,":[22],"this":[23],"article":[24],"presents":[25],"an":[26],"attentional":[27],"cross-domain":[28,69],"deep":[29,88],"architecture,":[30,171],"which":[31],"can":[32,118,197],"be":[33],"trained":[34],"end-to-end.":[35],"This":[36],"architecture":[37],"composed":[39],"three":[41,49],"convolutional":[42],"neural":[43],"network":[44,140],"(CNN)":[45],"streams":[46],"to":[47,74,78,142,156,211],"extract":[48],"types":[50,104,125,179],"features,":[52,60],"including":[53],"visual":[54],"perception,":[55],"resampling,":[56],"local":[58],"inconsistency":[59],"from":[61,82,107],"spatial":[62],"frequency":[64],"domains.":[65],"The":[66],"multitype":[67],"features":[70,77,106],"are":[71,149],"then":[72,150],"combined":[73],"formulate":[75],"hybrid":[76,164],"distinguish":[79],"manipulated":[80],"regions":[81],"nonmanipulated":[83],"parts.":[84,145],"Compared":[85],"other":[87],"architectures,":[89],"proposed":[91,170,195],"one":[92],"spans":[93],"a":[94,111,134,174],"more":[95],"complementary":[96],"discriminative":[98,138],"feature":[99],"space":[100],"by":[101,123],"integrating":[102],"richer":[103],"different":[108,124],"domains":[109],"in":[110],"unified":[112],"end-to-end":[113],"trainable":[114],"framework":[115],"thus":[117],"better":[119],"capture":[120],"artifacts":[121],"caused":[122],"manipulations.":[127],"In":[128],"addition,":[129],"we":[130,172],"design":[131],"train":[133,168],"module":[135],"called":[136],"attention":[139],"(TDA-Net)":[141],"highlight":[143],"suspicious":[144],"These":[146],"part-level":[147],"representations":[148],"integrated":[151],"global":[154],"ones":[155],"further":[157],"enhance":[158],"discriminating":[160],"capability":[161],"features.":[165],"adequately":[167],"synthesize":[173],"large":[175],"dataset":[176],"containing":[177],"various":[178,199],"manipulations":[181,200],"based":[182],"on":[183,188],"DRESDEN":[184],"COCO.":[186],"Experiments":[187],"four":[189],"public":[190],"datasets":[191],"demonstrate":[192],"that":[193],"model":[196],"localize":[198],"achieve":[202],"state-of-the-art":[204],"performance.":[205],"We":[206],"also":[207],"conduct":[208],"ablation":[209],"studies":[210],"verify":[212],"effectiveness":[214],"each":[216],"stream":[217],"TDA-Net":[220],"module.":[221]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2021-12-06T00:00:00"}
