{"id":"https://openalex.org/W2756305021","doi":"https://doi.org/10.1109/tip.2017.2752370","title":"Fundamental Principles on Learning New Features for Effective Dense Matching","display_name":"Fundamental Principles on Learning New Features for Effective Dense Matching","publication_year":2017,"publication_date":"2017-09-14","ids":{"openalex":"https://openalex.org/W2756305021","doi":"https://doi.org/10.1109/tip.2017.2752370","mag":"2756305021","pmid":"https://pubmed.ncbi.nlm.nih.gov/28920900"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2017.2752370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2017.2752370","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","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":"https://openalex.org/A5101421861","display_name":"Feihu Zhang","orcid":"https://orcid.org/0000-0003-0712-5722"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feihu Zhang","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080392568","display_name":"Benjamin W. Wah","orcid":"https://orcid.org/0000-0002-2335-3904"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Benjamin W. Wah","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101421861"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":2.4576,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.93871548,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"27","issue":"2","first_page":"822","last_page":"836"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9987999796867371,"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":0.996999979019165,"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":0.7178441882133484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.681830883026123},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5563141107559204},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.5494290590286255},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.505193293094635},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4825543761253357},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44993993639945984},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4343889057636261},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18393146991729736},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1786121428012848}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7178441882133484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.681830883026123},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5563141107559204},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.5494290590286255},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.505193293094635},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4825543761253357},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44993993639945984},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4343889057636261},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18393146991729736},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1786121428012848},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2017.2752370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2017.2752370","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:28920900","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28920900","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W1543403517","https://openalex.org/W1560740717","https://openalex.org/W1772650917","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1915301860","https://openalex.org/W1921093919","https://openalex.org/W1932937519","https://openalex.org/W1964057156","https://openalex.org/W1968799614","https://openalex.org/W1981765608","https://openalex.org/W1987411195","https://openalex.org/W1993120651","https://openalex.org/W2000083214","https://openalex.org/W2005570605","https://openalex.org/W2009250577","https://openalex.org/W2039580825","https://openalex.org/W2053467532","https://openalex.org/W2066941820","https://openalex.org/W2101431131","https://openalex.org/W2106334424","https://openalex.org/W2109255472","https://openalex.org/W2115579991","https://openalex.org/W2117248802","https://openalex.org/W2117444972","https://openalex.org/W2119605622","https://openalex.org/W2126105956","https://openalex.org/W2127317074","https://openalex.org/W2128357735","https://openalex.org/W2133255058","https://openalex.org/W2144041313","https://openalex.org/W2147253850","https://openalex.org/W2147800946","https://openalex.org/W2151103935","https://openalex.org/W2151646056","https://openalex.org/W2155655721","https://openalex.org/W2155893237","https://openalex.org/W2156380531","https://openalex.org/W2157431410","https://openalex.org/W2158919891","https://openalex.org/W2194775991","https://openalex.org/W2198098822","https://openalex.org/W2218190025","https://openalex.org/W2274287116","https://openalex.org/W2294238219","https://openalex.org/W2299400169","https://openalex.org/W2315032847","https://openalex.org/W2440384215","https://openalex.org/W2517490240","https://openalex.org/W2549139847","https://openalex.org/W2590620738","https://openalex.org/W2613818078","https://openalex.org/W2735676410","https://openalex.org/W2768066693","https://openalex.org/W2949117887","https://openalex.org/W2953328958","https://openalex.org/W2963219046","https://openalex.org/W2963502507","https://openalex.org/W2963891150","https://openalex.org/W2964350391","https://openalex.org/W2981061699","https://openalex.org/W4214920538","https://openalex.org/W4300860510","https://openalex.org/W6638039622","https://openalex.org/W6660133353","https://openalex.org/W6679144564","https://openalex.org/W6726452804"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W4390494008","https://openalex.org/W2922442631","https://openalex.org/W2053596378","https://openalex.org/W2168523118","https://openalex.org/W2762689969"],"abstract_inverted_index":{"In":[0,75],"dense":[1,100,120],"matching":[2,5,32,60,101,155],"(including":[3],"stereo":[4,154,186],"and":[6,87,133,153,188],"optical":[7,151],"flow),":[8],"nearly":[9],"all":[10,96],"existing":[11,97,193],"approaches":[12],"are":[13,102],"based":[14,83,128],"on":[15,84,129,144,175,183,197],"simple":[16,26],"features,":[17],"such":[18,57],"as":[19,58,156],"gray":[20],"or":[21,25,64,109],"RGB":[22],"color,":[23],"gradient":[24],"transformations":[27],"like":[28],"census,":[29],"to":[30,138],"calculate":[31],"costs.":[33],"These":[34],"features":[35,105,118,141,164],"do":[36],"not":[37],"perform":[38],"well":[39],"in":[40,99],"complex":[41],"scenes":[42],"that":[43,94,106,142,162],"may":[44,55],"involve":[45],"radiometric":[46],"changes,":[47],"noises,":[48],"overexposure":[49],"and/or":[50,70],"textureless":[51],"regions.":[52],"Various":[53],"problems":[54,98],"appear,":[56],"wrong":[59],"at":[61],"the":[62,85,88,145,163,169,176,184,190],"pixel":[63],"region":[65],"level,":[66],"flattening/breaking":[67],"of":[68,90,111,171],"edges":[69],"even":[71],"entire":[72],"structural":[73],"collapse.":[74],"this":[76],"paper,":[77],"we":[78,122],"propose":[79],"two":[80,131,185],"fundamental":[81],"principles":[82,132],"consistency":[86],"distinctiveness":[89],"features.":[91],"We":[92],"show":[93,161],"almost":[95],"caused":[103],"by":[104],"violate":[107],"one":[108],"both":[110],"these":[112,130],"principles.":[113],"To":[114],"systematically":[115],"learn":[116],"good":[117],"for":[119],"matching,":[121],"develop":[123],"a":[124],"general":[125],"multi-objective":[126],"optimization":[127],"apply":[134],"convolutional":[135],"neural":[136],"networks":[137],"find":[139],"new":[140],"lie":[143],"Pareto":[146],"frontier.":[147],"By":[148],"using":[149],"two-frame":[150,194],"flow":[152,198],"applications,":[157],"our":[158,179],"experimental":[159],"results":[160],"learned":[165],"can":[166],"significantly":[167],"improve":[168],"performance":[170],"state-of-the-art":[172],"approaches.":[173],"Based":[174],"KITTI":[177],"benchmarks,":[178],"method":[180],"ranks":[181],"first":[182],"benchmarks":[187],"is":[189],"best":[191],"among":[192],"optical-flow":[195],"algorithms":[196],"benchmarks.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}