{"id":"https://openalex.org/W4366293506","doi":"https://doi.org/10.1007/s41095-022-0294-4","title":"Discriminative feature encoding for intrinsic image decomposition","display_name":"Discriminative feature encoding for intrinsic image decomposition","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4366293506","doi":"https://doi.org/10.1007/s41095-022-0294-4"},"language":"en","primary_location":{"id":"doi:10.1007/s41095-022-0294-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-022-0294-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-022-0294-4.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s41095-022-0294-4.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063279247","display_name":"Zongji Wang","orcid":"https://orcid.org/0000-0001-9684-300X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongji Wang","raw_affiliation_strings":["Key Laboratory of Network Information System Technology (NIST), Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China","Key Laboratory of Network Information System Technology (NIST), Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Network Information System Technology (NIST), Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"raw_affiliation_string":"Key Laboratory of Network Information System Technology (NIST), Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100704143","display_name":"Yunfei Liu","orcid":"https://orcid.org/0000-0001-6898-0058"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfei Liu","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing 100191, China","State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050527785","display_name":"Feng Lu","orcid":"https://orcid.org/0000-0001-9064-7964"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Lu","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing 100191, China; Peng Cheng Laboratory, Shenzhen 518000, China","State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing 100191, China; Peng Cheng Laboratory, Shenzhen 518000, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing, 100191, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5050527785"],"corresponding_institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I82880672"],"apc_list":{"value":0,"currency":"USD","value_usd":0},"apc_paid":null,"fwci":1.045,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.7491534,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"9","issue":"3","first_page":"597","last_page":"618"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9997000098228455,"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":0.9997000098228455,"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/discriminative-model","display_name":"Discriminative model","score":0.7196959853172302},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.708137035369873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6637787818908691},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.6287449598312378},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5967851877212524},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5771499872207642},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5569936037063599},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.49283432960510254},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49069058895111084},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4587329924106598},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics","score":0.45724985003471375},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4479863941669464},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4330301284790039},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3698654770851135},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33040791749954224}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7196959853172302},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.708137035369873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6637787818908691},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.6287449598312378},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5967851877212524},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5771499872207642},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5569936037063599},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.49283432960510254},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49069058895111084},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4587329924106598},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.45724985003471375},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4479863941669464},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4330301284790039},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3698654770851135},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33040791749954224},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s41095-022-0294-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-022-0294-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-022-0294-4.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:01da38f739cb4f7bb5b4e407762fbfd9","is_oa":true,"landing_page_url":"https://doaj.org/article/01da38f739cb4f7bb5b4e407762fbfd9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Visual Media, Vol 9, Iss 3, Pp 597-618 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s41095-022-0294-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-022-0294-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-022-0294-4.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G3570431576","display_name":null,"funder_award_id":"61972012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6560199936","display_name":null,"funder_award_id":"61732016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4366293506.pdf","grobid_xml":"https://content.openalex.org/works/W4366293506.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W186865409","https://openalex.org/W1513100184","https://openalex.org/W1583837637","https://openalex.org/W1923848918","https://openalex.org/W1934235358","https://openalex.org/W1980212291","https://openalex.org/W1994246617","https://openalex.org/W2002193550","https://openalex.org/W2010812559","https://openalex.org/W2027560260","https://openalex.org/W2053186076","https://openalex.org/W2076491823","https://openalex.org/W2080794127","https://openalex.org/W2083779601","https://openalex.org/W2087257250","https://openalex.org/W2101856619","https://openalex.org/W2104166077","https://openalex.org/W2108598243","https://openalex.org/W2113404166","https://openalex.org/W2117751343","https://openalex.org/W2133661850","https://openalex.org/W2133665775","https://openalex.org/W2136748901","https://openalex.org/W2164847484","https://openalex.org/W2193045528","https://openalex.org/W2199820243","https://openalex.org/W2220470871","https://openalex.org/W2221366145","https://openalex.org/W2303211814","https://openalex.org/W2331128040","https://openalex.org/W2468336759","https://openalex.org/W2468596194","https://openalex.org/W2567309586","https://openalex.org/W2583983165","https://openalex.org/W2608400466","https://openalex.org/W2765302960","https://openalex.org/W2802922942","https://openalex.org/W2888277922","https://openalex.org/W2890958373","https://openalex.org/W2891279733","https://openalex.org/W2905601289","https://openalex.org/W2911293880","https://openalex.org/W2952972288","https://openalex.org/W2963395931","https://openalex.org/W2964321964","https://openalex.org/W2965189593","https://openalex.org/W2985810937","https://openalex.org/W2990896888","https://openalex.org/W2991176674","https://openalex.org/W2998637570","https://openalex.org/W3129301603","https://openalex.org/W3156899835","https://openalex.org/W3164884113","https://openalex.org/W3181444857","https://openalex.org/W3185905868","https://openalex.org/W4214948749","https://openalex.org/W4254903059"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W4223917824","https://openalex.org/W156213964"],"abstract_inverted_index":{"Intrinsic":[0],"image":[1,40,155],"decomposition":[2,165],"is":[3,20,139,159],"an":[4,12,80],"important":[5],"and":[6,49],"long-standing":[7],"computer":[8,57],"vision":[9,58],"problem.":[10],"Given":[11],"input":[13,81],"image,":[14],"recovering":[15],"the":[16,31,35,67,89,97,110,125,146,183],"physical":[17],"scene":[18],"properties":[19],"ill-posed.":[21],"Several":[22],"physically":[23],"motivated":[24],"priors":[25],"have":[26],"been":[27],"used":[28],"to":[29,71,107,123,141,162],"restrict":[30],"solution":[32],"space":[33],"of":[34,46,92,113],"optimization":[36],"problem":[37,59],"for":[38,75,153],"intrinsic":[39,77,94,115,154,163],"decomposition.":[41,156],"This":[42],"work":[43],"takes":[44],"advantage":[45],"deep":[47],"learning,":[48],"shows":[50],"that":[51,176],"it":[52,150],"can":[53,181],"solve":[54],"this":[55,85],"challenging":[56],"with":[60],"high":[61],"efficiency.":[62],"The":[63,117],"focus":[64],"lies":[65],"in":[66,96],"feature":[68,99,104,111,118,130],"encoding":[69],"phase":[70],"extract":[72],"discriminative":[73],"features":[74],"different":[76,93,114],"layers":[78],"from":[79,145],"image.":[82],"To":[83],"achieve":[84],"goal,":[86],"we":[87],"explore":[88],"distinctive":[90],"characteristics":[91],"components":[95],"high-dimensional":[98],"embedding":[100],"space.":[101],"We":[102],"define":[103],"distribution":[105,131],"divergence":[106],"efficiently":[108],"separate":[109],"vectors":[112],"components.":[116],"distributions":[119],"are":[120],"also":[121,160],"constrained":[122],"fit":[124],"real":[126],"ones":[127],"through":[128],"a":[129,135],"consistency.":[132],"In":[133],"addition,":[134],"data":[136,143],"refinement":[137],"approach":[138],"provided":[140],"remove":[142],"inconsistency":[144],"Sintel":[147],"dataset,":[148],"making":[149],"more":[151],"suitable":[152],"Our":[157],"method":[158],"extended":[161],"video":[164],"based":[166],"on":[167],"pixel-wise":[168],"correspondences":[169],"between":[170],"adjacent":[171],"frames.":[172],"Experimental":[173],"results":[174],"indicate":[175],"our":[177],"proposed":[178],"network":[179],"structure":[180],"outperform":[182],"existing":[184],"state-of-the-art.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
