{"id":"https://openalex.org/W1926022583","doi":"https://doi.org/10.1109/cvpr.2015.7298822","title":"DASC: Dense adaptive self-correlation descriptor for multi-modal and multi-spectral correspondence","display_name":"DASC: Dense adaptive self-correlation descriptor for multi-modal and multi-spectral correspondence","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1926022583","doi":"https://doi.org/10.1109/cvpr.2015.7298822","mag":"1926022583"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7298822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5085363061","display_name":"Seungryong Kim","orcid":"https://orcid.org/0000-0003-2927-6273"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Seungryong Kim","raw_affiliation_strings":["Yonsei University"],"affiliations":[{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037006973","display_name":"Dongbo Min","orcid":"https://orcid.org/0000-0003-4825-5240"},"institutions":[{"id":"https://openalex.org/I196345858","display_name":"Chungnam National University","ror":"https://ror.org/0227as991","country_code":"KR","type":"education","lineage":["https://openalex.org/I196345858"]},{"id":"https://openalex.org/I4210089174","display_name":"Area Detector Systems Corporation (United States)","ror":"https://ror.org/00a1a0x11","country_code":"US","type":"company","lineage":["https://openalex.org/I4210089174"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Dongbo Min","raw_affiliation_strings":["ADSC","Chungnam Nat. University"],"affiliations":[{"raw_affiliation_string":"ADSC","institution_ids":["https://openalex.org/I4210089174"]},{"raw_affiliation_string":"Chungnam Nat. University","institution_ids":["https://openalex.org/I196345858"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054888241","display_name":"Bumsub Ham","orcid":"https://orcid.org/0000-0002-3443-8161"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en informatique et en automatique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1326498283"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Bumsub Ham","raw_affiliation_strings":["Inria"],"affiliations":[{"raw_affiliation_string":"Inria","institution_ids":["https://openalex.org/I1326498283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102080545","display_name":"Seungchul Ryu","orcid":null},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungchul Ryu","raw_affiliation_strings":["Yonsei University"],"affiliations":[{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005908865","display_name":"N. Minh","orcid":"https://orcid.org/0000-0001-5132-4986"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minh N. Do","raw_affiliation_strings":["SUIUC"],"affiliations":[{"raw_affiliation_string":"SUIUC","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073320959","display_name":"Kwanghoon Sohn","orcid":"https://orcid.org/0000-0002-3715-0331"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kwanghoon Sohn","raw_affiliation_strings":["Yonsei University"],"affiliations":[{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5085363061"],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":6.6274,"has_fulltext":false,"cited_by_count":82,"citation_normalized_percentile":{"value":0.97794044,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2103","last_page":"2112"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T10531","display_name":"Advanced Vision and Imaging","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9983999729156494,"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/computer-science","display_name":"Computer science","score":0.7587347030639648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7195874452590942},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5958175659179688},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5347411036491394},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5327140688896179},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5153235793113708},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5025498867034912},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4954754114151001},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.44122952222824097},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.44036561250686646},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2797618508338928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1958664059638977}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7587347030639648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7195874452590942},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5958175659179688},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5347411036491394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5327140688896179},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5153235793113708},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5025498867034912},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4954754114151001},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.44122952222824097},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.44036561250686646},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2797618508338928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1958664059638977},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2015.7298822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.75,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1506898119","https://openalex.org/W1513100184","https://openalex.org/W1674866864","https://openalex.org/W1968799614","https://openalex.org/W1983592655","https://openalex.org/W1990654150","https://openalex.org/W1992060453","https://openalex.org/W1995266040","https://openalex.org/W1995813543","https://openalex.org/W2001002651","https://openalex.org/W2012893378","https://openalex.org/W2019085623","https://openalex.org/W2019904315","https://openalex.org/W2033959528","https://openalex.org/W2034872721","https://openalex.org/W2038675879","https://openalex.org/W2043075591","https://openalex.org/W2060613391","https://openalex.org/W2062415280","https://openalex.org/W2065533005","https://openalex.org/W2090518410","https://openalex.org/W2097934584","https://openalex.org/W2104853049","https://openalex.org/W2104974755","https://openalex.org/W2105466713","https://openalex.org/W2106505277","https://openalex.org/W2120339103","https://openalex.org/W2124861766","https://openalex.org/W2125188192","https://openalex.org/W2129317273","https://openalex.org/W2130951370","https://openalex.org/W2131747574","https://openalex.org/W2143516773","https://openalex.org/W2144502914","https://openalex.org/W2144531167","https://openalex.org/W2151103935","https://openalex.org/W2153635508","https://openalex.org/W2154194773","https://openalex.org/W2156875677","https://openalex.org/W2160451035","https://openalex.org/W2161969291","https://openalex.org/W2164517370","https://openalex.org/W4232454059","https://openalex.org/W6630726011","https://openalex.org/W6653714346","https://openalex.org/W6673243404","https://openalex.org/W6674774244","https://openalex.org/W6679572048","https://openalex.org/W6681426593"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W2965546495","https://openalex.org/W3211292372"],"abstract_inverted_index":{"Establishing":[0],"dense":[1,26,67,71],"visual":[2,50],"correspondence":[3,51],"between":[4],"multiple":[5],"images":[6,33,56,92],"is":[7,93,139,160],"a":[8,65,88,104,114,129,136,142],"fundamental":[9],"task":[10],"in":[11,35,38,44,52,134,177],"many":[12,178],"applications":[13],"of":[14,80,106,173,180],"computer":[15],"vision":[16],"and":[17,28,124,182],"computational":[18,147],"photography.":[19],"Classical":[20],"approaches,":[21],"which":[22,135],"aim":[23],"to":[24,75,96],"estimate":[25],"stereo":[27],"optical":[29],"flow":[30],"fields":[31],"for":[32,111],"adjacent":[34],"viewpoint":[36],"or":[37,54],"time,":[39],"have":[40],"been":[41],"dramatically":[42,161],"advanced":[43],"recent":[45],"studies.":[46],"However,":[47],"finding":[48],"reliable":[49],"multi-modal":[53,181],"multi-spectral":[55,183],"still":[57],"remains":[58],"unsolved.":[59],"In":[60],"this":[61,78],"paper,":[62],"we":[63,99,127],"propose":[64,128],"novel":[66],"matching":[68,81,122],"descriptor,":[69],"called":[70],"adaptive":[72,108],"self-correlation":[73,109],"(DASC),":[74],"effectively":[76],"address":[77],"kind":[79],"scenarios.":[82],"Based":[83],"on":[84],"the":[85,101,121,146,170,174],"observation":[86],"that":[87,149],"self-similarity":[89],"existing":[90],"within":[91,113],"less":[94],"sensitive":[95],"modality":[97],"variations,":[98],"define":[100],"descriptor":[102,155,176],"with":[103,141],"series":[105],"an":[107,157],"similarity":[110],"patches":[112],"local":[115],"support":[116],"window.":[117],"To":[118],"further":[119],"improve":[120],"quality":[123],"runtime":[125],"efficiency,":[126],"randomized":[130],"receptive":[131],"field":[132],"pooling,":[133],"sampling":[137],"pattern":[138],"optimized":[140],"discriminative":[143],"learning.":[144],"Moreover,":[145],"redundancy":[148],"arises":[150],"when":[151],"computing":[152],"densely":[153],"sampled":[154],"over":[156],"entire":[158],"image":[159],"reduced":[162],"by":[163],"applying":[164],"fast":[165],"edge-aware":[166],"filtering.":[167],"Experiments":[168],"demonstrate":[169],"outstanding":[171],"performance":[172],"DASC":[175],"cases":[179],"correspondence.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":11},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}