{"id":"https://openalex.org/W4415540987","doi":"https://doi.org/10.1145/3746027.3755664","title":"DenseSR: Image Shadow Removal as Dense Prediction","display_name":"DenseSR: Image Shadow Removal as Dense Prediction","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415540987","doi":"https://doi.org/10.1145/3746027.3755664"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755664","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755664","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd 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/A5112016220","display_name":"Yu-Fan Lin","orcid":"https://orcid.org/0009-0000-9459-701X"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yu-Fan Lin","raw_affiliation_strings":["National Cheng Kung University, Tainan, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034075233","display_name":"Chia-Ming Lee","orcid":"https://orcid.org/0009-0004-6027-3083"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chia-Ming Lee","raw_affiliation_strings":["National Cheng Kung University, Tainan, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007305393","display_name":"Chih\u2013Chung Hsu","orcid":"https://orcid.org/0000-0002-2083-4438"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Chung Hsu","raw_affiliation_strings":["National Yang Ming Chiao Tung University, Tainan, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112016220"],"corresponding_institution_ids":["https://openalex.org/I91807558"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30809266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7026","last_page":"7035"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994999766349792,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994999766349792,"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":0.9984999895095825,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9983999729156494,"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/image-restoration","display_name":"Image restoration","score":0.6498000025749207},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.604200005531311},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5501000285148621},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5347999930381775},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5267999768257141},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5202000141143799},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4950000047683716},{"id":"https://openalex.org/keywords/shadow","display_name":"Shadow (psychology)","score":0.4733999967575073},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.47290000319480896}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.698199987411499},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6525999903678894},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.6498000025749207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6474999785423279},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.604200005531311},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5501000285148621},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5347999930381775},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5267999768257141},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5202000141143799},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4950000047683716},{"id":"https://openalex.org/C117797892","wikidata":"https://www.wikidata.org/wiki/Q286363","display_name":"Shadow (psychology)","level":2,"score":0.4733999967575073},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.47290000319480896},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.45910000801086426},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.40450000762939453},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.373199999332428},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35569998621940613},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2784000039100647},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.26100000739097595}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755664","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755664","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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":35,"referenced_works":["https://openalex.org/W1541667274","https://openalex.org/W1901129140","https://openalex.org/W2035234709","https://openalex.org/W2060850257","https://openalex.org/W2123009513","https://openalex.org/W2143373691","https://openalex.org/W2395611524","https://openalex.org/W2476548250","https://openalex.org/W2565639579","https://openalex.org/W2801375052","https://openalex.org/W2807784014","https://openalex.org/W2963014378","https://openalex.org/W2963150697","https://openalex.org/W2985036575","https://openalex.org/W2998154526","https://openalex.org/W3096609285","https://openalex.org/W3131500599","https://openalex.org/W3133630855","https://openalex.org/W3138516171","https://openalex.org/W3153006434","https://openalex.org/W4214520160","https://openalex.org/W4250928359","https://openalex.org/W4312812783","https://openalex.org/W4312896979","https://openalex.org/W4312977443","https://openalex.org/W4323064867","https://openalex.org/W4385275512","https://openalex.org/W4385486286","https://openalex.org/W4385804897","https://openalex.org/W4390873058","https://openalex.org/W4392909584","https://openalex.org/W4402904061","https://openalex.org/W4402917035","https://openalex.org/W4402917251","https://openalex.org/W4403791954"],"related_works":[],"abstract_inverted_index":{"Shadows":[0],"are":[1,152],"a":[2,69,104,129],"common":[3],"factor":[4],"degrading":[5],"image":[6],"quality.":[7,76],"Single-image":[8],"shadow":[9],"removal":[10],"(SR),":[11],"particularly":[12],"under":[13],"challenging":[14],"indirect":[15],"illumination,":[16],"is":[17],"hampered":[18],"by":[19,89],"non-uniform":[20],"content":[21],"degradation":[22],"and":[23,36,44,52,95,99,128,137,145,163],"inherent":[24],"ambiguity.":[25],"Consequently,":[26],"traditional":[27],"methods":[28],"often":[29],"fail":[30],"to":[31,73,92],"simultaneously":[32],"recover":[33],"intra-shadow":[34],"details":[35],"maintain":[37],"sharp":[38,138],"boundaries,":[39],"resulting":[40],"in":[41,110],"inconsistent":[42,143],"restoration":[43,75,102,144],"blurring":[45,146],"that":[46],"negatively":[47],"affect":[48],"both":[49,161],"downstream":[50],"applications":[51],"the":[53,63,66,111,142,169],"overall":[54],"viewing":[55],"experience.":[56],"To":[57],"overcome":[58],"these":[59],"limitations,":[60],"we":[61],"propose":[62],"DenseSR,":[64],"approaching":[65],"problem":[67],"from":[68],"dense":[70],"prediction":[71],"perspective":[72],"emphasize":[74],"This":[77],"framework":[78],"uniquely":[79],"synergizes":[80],"two":[81],"key":[82],"strategies:":[83],"(1)":[84],"deep":[85],"scene":[86],"understanding":[87],"guided":[88],"geometric-semantic":[90],"priors":[91],"resolve":[93],"ambiguity":[94],"implicitly":[96],"localize":[97],"shadows,":[98],"(2)":[100],"high-fidelity":[101],"via":[103],"novel":[105],"Dense":[106],"Fusion":[107],"Block":[108],"(DFB)":[109],"decoder.":[112],"The":[113],"DFB":[114],"employs":[115],"adaptive":[116],"component":[117],"processing-using":[118],"an":[119,156],"Adaptive":[120],"Content":[121],"Smoothing":[122],"Module":[123,132],"(ACSM)":[124],"for":[125,134],"consistent":[126],"appearance":[127],"Texture-Boundary":[130],"Recuperation":[131],"(TBRM)":[133],"fine":[135],"textures":[136],"boundaries-thereby":[139],"directly":[140],"tackling":[141],"issues.":[147],"These":[148],"purposefully":[149],"processed":[150],"components":[151],"effectively":[153],"fused,":[154],"yielding":[155],"optimized":[157],"feature":[158],"representation":[159],"preserving":[160],"consistency":[162],"fidelity.":[164],"Extensive":[165],"experimental":[166],"results":[167],"demonstrate":[168],"merits":[170],"of":[171],"our":[172],"approach":[173],"over":[174],"existing":[175],"methods.":[176],"Our":[177],"code":[178],"can":[179],"be":[180],"available":[181],"on":[182],"https://github.com/VanLinLin/DenseSR":[183]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-25T00:00:00"}