{"id":"https://openalex.org/W3205675531","doi":"https://doi.org/10.1145/3474085.3475205","title":"Mix-order Attention Networks for Image Restoration","display_name":"Mix-order Attention Networks for Image Restoration","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W3205675531","doi":"https://doi.org/10.1145/3474085.3475205","mag":"3205675531"},"language":"en","primary_location":{"id":"doi:10.1145/3474085.3475205","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Multimedia","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/A5023762528","display_name":"Tao Dai","orcid":"https://orcid.org/0000-0003-0594-6404"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Dai","raw_affiliation_strings":["Shenzhen University, Shenzhen , China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen , China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112639583","display_name":"Yalei Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalei Lv","raw_affiliation_strings":["Tsinghua University, Shenzhen , China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen , China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427338","display_name":"Bin Chen","orcid":"https://orcid.org/0000-0002-4798-230X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Chen","raw_affiliation_strings":["Tsinghua University, Shenzhen , China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen , China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100376399","display_name":"Zhi Wang","orcid":"https://orcid.org/0000-0002-5462-6178"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Wang","raw_affiliation_strings":["Tsinghua University, Shenzhen , China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen , China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052762681","display_name":"Zexuan Zhu","orcid":"https://orcid.org/0000-0001-8479-6904"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zexuan Zhu","raw_affiliation_strings":["Shenzhen University, Shenzhen , China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen , China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034104790","display_name":"Shu\u2010Tao Xia","orcid":"https://orcid.org/0000-0002-8639-982X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu-Tao Xia","raw_affiliation_strings":["Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5023762528"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.2882,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.56320261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2880","last_page":"2888"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9995999932289124,"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":0.9937000274658203,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7524844408035278},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7134908437728882},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.685611367225647},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6232456564903259},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.6098291873931885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.56479412317276},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5246548652648926},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5027916431427002},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.4985027313232422},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4819328784942627},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.4577372074127197},{"id":"https://openalex.org/keywords/demosaicing","display_name":"Demosaicing","score":0.44649189710617065},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.43696528673171997},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43682193756103516},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4310777485370636},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2952827215194702},{"id":"https://openalex.org/keywords/color-image","display_name":"Color image","score":0.10777956247329712}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7524844408035278},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7134908437728882},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.685611367225647},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6232456564903259},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.6098291873931885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.56479412317276},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5246548652648926},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5027916431427002},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.4985027313232422},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4819328784942627},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.4577372074127197},{"id":"https://openalex.org/C27624317","wikidata":"https://www.wikidata.org/wiki/Q263499","display_name":"Demosaicing","level":5,"score":0.44649189710617065},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.43696528673171997},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43682193756103516},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4310777485370636},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2952827215194702},{"id":"https://openalex.org/C142616399","wikidata":"https://www.wikidata.org/wiki/Q5148604","display_name":"Color image","level":4,"score":0.10777956247329712},{"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},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3474085.3475205","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W10548402","https://openalex.org/W1885185971","https://openalex.org/W1906770428","https://openalex.org/W1930824406","https://openalex.org/W2025768430","https://openalex.org/W2047710600","https://openalex.org/W2121927366","https://openalex.org/W2133665775","https://openalex.org/W2142683286","https://openalex.org/W2242218935","https://openalex.org/W2508457857","https://openalex.org/W2520164769","https://openalex.org/W2601789736","https://openalex.org/W2613155248","https://openalex.org/W2739757502","https://openalex.org/W2752782242","https://openalex.org/W2780544323","https://openalex.org/W2799265886","https://openalex.org/W2866634454","https://openalex.org/W2884751099","https://openalex.org/W2912268344","https://openalex.org/W2947156405","https://openalex.org/W2954930822","https://openalex.org/W2963091558","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963495494","https://openalex.org/W2963550079","https://openalex.org/W2963610452","https://openalex.org/W2963729050","https://openalex.org/W2964101377","https://openalex.org/W2964125708","https://openalex.org/W2964277374","https://openalex.org/W4252054347"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2080784917","https://openalex.org/W2626256601","https://openalex.org/W3105037121","https://openalex.org/W4211167461","https://openalex.org/W3200694817","https://openalex.org/W3131362257","https://openalex.org/W2968664063","https://openalex.org/W4254875156","https://openalex.org/W3152929143"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2,57],"(CNNs)":[3],"have":[4],"obtained":[5],"great":[6],"success":[7],"in":[8,32,147],"image":[9,14,28,115,127,131],"restoration":[10,128],"tasks,":[11,129],"like":[12,130],"single":[13],"denoising,":[15,132],"demosaicing,":[16],"and":[17,30,36,78,91,117,134,151],"super-resolution.":[18],"However,":[19],"most":[20],"existing":[21],"CNN-based":[22],"methods":[23,146],"neglect":[24],"the":[25,33,43],"diversity":[26],"of":[27,46,88,99,114,149],"contents":[29,116],"degradations":[31],"corrupted":[34],"images":[35],"treat":[37],"channel-wise":[38],"features":[39,61],"equally,":[40],"thus":[41],"hindering":[42],"representation":[44],"ability":[45],"CNNs.":[47],"To":[48],"address":[49],"this":[50],"issue,":[51],"we":[52],"propose":[53],"deep":[54],"mix-order":[55,80],"attention":[56,82],"(MAN)":[58],"to":[59,95,110,125],"extract":[60],"that":[62,139],"capture":[63,96],"rich":[64],"feature":[65,89,92],"statistics":[66],"within":[67],"networks.":[68],"Our":[69],"MAN":[70,106,121],"is":[71],"mainly":[72],"built":[73],"on":[74],"simple":[75],"residual":[76],"blocks":[77,94],"our":[79,103,105,120,140],"channel":[81],"(MOCA)":[83],"module,":[84],"which":[85],"further":[86],"consists":[87],"gating":[90],"pooling":[93],"different":[97,126],"types":[98,113],"semantic":[100],"information.":[101],"With":[102],"MOCA,":[104],"can":[107,122],"be":[108,123],"flexible":[109],"handle":[111],"various":[112],"degradations.":[118],"Besides,":[119],"generalized":[124],"super-resolution,":[133],"demosaicing.":[135],"Extensive":[136],"experiments":[137],"demonstrate":[138],"method":[141],"obtains":[142],"favorably":[143],"against":[144],"state-of-the-art":[145],"terms":[148],"quantitative":[150],"qualitative":[152],"metrics.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}