{"id":"https://openalex.org/W3015516611","doi":"https://doi.org/10.1109/icassp40776.2020.9054068","title":"A Dense U-Net with Cross-Layer Intersection for Detection and Localization of Image Forgery","display_name":"A Dense U-Net with Cross-Layer Intersection for Detection and Localization of Image Forgery","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015516611","doi":"https://doi.org/10.1109/icassp40776.2020.9054068","mag":"3015516611"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9054068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5101803269","display_name":"Rongyu Zhang","orcid":"https://orcid.org/0000-0002-9174-1765"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rongyu Zhang","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-Sen University, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-Sen University, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039213686","display_name":"Jiangqun Ni","orcid":"https://orcid.org/0000-0002-7520-9031"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangqun Ni","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-Sen University, China"],"affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-Sen University, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101803269"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":3.3217,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.9359918,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2982","last_page":"2986"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":1.0,"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":1.0,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9890999794006348,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","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"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.9250576496124268},{"id":"https://openalex.org/keywords/concatenation","display_name":"Concatenation (mathematics)","score":0.7478591203689575},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.7309778928756714},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7222833633422852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.662392258644104},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5599666833877563},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.524451494216919},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5167738199234009},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5155901312828064},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5048988461494446},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.49592575430870056},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4888541102409363},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48410069942474365},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.45320868492126465},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44877374172210693},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.42016133666038513},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2943829298019409},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19540226459503174}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9250576496124268},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.7478591203689575},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.7309778928756714},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7222833633422852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.662392258644104},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5599666833877563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.524451494216919},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5167738199234009},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5155901312828064},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5048988461494446},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.49592575430870056},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4888541102409363},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48410069942474365},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.45320868492126465},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44877374172210693},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.42016133666038513},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2943829298019409},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19540226459503174},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9054068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9054068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5400000214576721,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1971111339","https://openalex.org/W2009130368","https://openalex.org/W2096076665","https://openalex.org/W2097506049","https://openalex.org/W2104116677","https://openalex.org/W2111374353","https://openalex.org/W2158972589","https://openalex.org/W2169439181","https://openalex.org/W2345213863","https://openalex.org/W2541922885","https://openalex.org/W2572561073","https://openalex.org/W2605252717","https://openalex.org/W2752015292","https://openalex.org/W2890429900","https://openalex.org/W2963446712","https://openalex.org/W2963777235","https://openalex.org/W2964146055","https://openalex.org/W6639824700"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2373577936","https://openalex.org/W4221148444","https://openalex.org/W4387678054","https://openalex.org/W2389596151","https://openalex.org/W3095575180","https://openalex.org/W2607795551","https://openalex.org/W4306784355","https://openalex.org/W3155117723","https://openalex.org/W1991429770"],"abstract_inverted_index":{"In":[0,65],"this":[1],"paper,":[2],"we":[3,40],"apply":[4],"cross-layer":[5],"intersection":[6],"mechanism":[7],"to":[8,45,78,93],"dense":[9],"u-net":[10],"for":[11,21,31,62],"image":[12,63],"forgery":[13],"detection":[14],"and":[15,54,76,84],"localization.":[16],"We":[17],"first":[18],"train":[19],"DenseNet":[20],"binary":[22],"classification.":[23],"Spatial":[24],"rich":[25],"model":[26],"(SRM)":[27],"filters":[28],"are":[29,72],"adopted":[30],"capturing":[32],"residual":[33],"signals":[34],"in":[35,69],"the":[36,58,95,98,105],"detected":[37],"images.":[38],"Then":[39],"propose":[41],"a":[42],"new":[43],"approach":[44],"preserve":[46],"complete":[47],"feature":[48],"maps":[49],"of":[50,97],"fully":[51],"connected":[52],"layer":[53],"consider":[55],"them":[56],"as":[57],"spatial":[59],"decision":[60],"information":[61],"segmentation.":[64],"addition,":[66],"these":[67],"features":[68],"downsampling":[70],"path":[71,80],"transferred":[73],"more":[74],"effectively":[75],"densely":[77],"upsampling":[79,83],"through":[81],"multiscale":[82],"concatenation.":[85],"A":[86],"multi-stage":[87],"training":[88],"scheme":[89],"is":[90],"then":[91],"applied":[92],"improve":[94],"convergence":[96],"network.":[99],"The":[100],"experimental":[101],"results":[102],"show":[103],"that":[104],"proposed":[106],"method":[107],"works":[108],"well":[109],"on":[110],"several":[111],"standard":[112],"datasets.":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":1}],"updated_date":"2026-02-11T14:41:00.668223","created_date":"2025-10-10T00:00:00"}