{"id":"https://openalex.org/W7162501432","doi":"https://doi.org/10.1109/3dv69130.2026.00019","title":"Structure-Grounded Training Strategies Aid Generalization in Stereo Matching","display_name":"Structure-Grounded Training Strategies Aid Generalization in Stereo Matching","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W7162501432","doi":"https://doi.org/10.1109/3dv69130.2026.00019"},"language":null,"primary_location":{"id":"doi:10.1109/3dv69130.2026.00019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","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/A5110983129","display_name":"Liangxun Ou","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Liangxun Ou","raw_affiliation_strings":["The University of Hong Kong,Hong Kong SAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Hong Kong SAR","institution_ids":["https://openalex.org/I177725633","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006094519","display_name":"Yuhui Liu","orcid":"https://orcid.org/0000-0003-3225-2088"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuhui Liu","raw_affiliation_strings":["The University of Hong Kong,Hong Kong SAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Hong Kong SAR","institution_ids":["https://openalex.org/I177725633","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001893388","display_name":"Zhenyang Li","orcid":"https://orcid.org/0000-0002-4694-1231"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhenyang Li","raw_affiliation_strings":["The University of Hong Kong,Hong Kong SAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Hong Kong SAR","institution_ids":["https://openalex.org/I177725633","https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125138459","display_name":"Xiaoyang Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaoyang Bai","raw_affiliation_strings":["The University of Hong Kong,Hong Kong SAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Hong Kong SAR","institution_ids":["https://openalex.org/I177725633","https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5137102828","display_name":"Yifan Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yifan Peng","raw_affiliation_strings":["The University of Hong Kong,Hong Kong SAR"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong,Hong Kong SAR","institution_ids":["https://openalex.org/I177725633","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.85242339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"125","last_page":"134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.11190000176429749,"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":0.11190000176429749,"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":0.08259999752044678,"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/T10860","display_name":"Speech and Audio Processing","score":0.0697999969124794,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/generalization","display_name":"Generalization","score":0.5726000070571899},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.49570000171661377},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4869999885559082},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.30799999833106995},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.2948000133037567}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6456999778747559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5849000215530396},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5726000070571899},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.49570000171661377},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49559998512268066},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4869999885559082},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2948000133037567},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/3dv69130.2026.00019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5089411495","display_name":null,"funder_award_id":"62322217","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5311240010","display_name":null,"funder_award_id":"ITP/062/24AP,MHP/313/24","funder_id":"https://openalex.org/F4320326427","funder_display_name":"Innovation and Technology Fund"},{"id":"https://openalex.org/G854411490","display_name":null,"funder_award_id":"17208023","funder_id":"https://openalex.org/F4320306709","funder_display_name":"Glaucoma Research Foundation"}],"funders":[{"id":"https://openalex.org/F4320306709","display_name":"Glaucoma Research Foundation","ror":"https://ror.org/05ez53b31"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326427","display_name":"Innovation and Technology Fund","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W63091017","https://openalex.org/W1921093919","https://openalex.org/W2115579991","https://openalex.org/W2150066425","https://openalex.org/W2259424905","https://openalex.org/W2412782625","https://openalex.org/W2604231069","https://openalex.org/W2741885505","https://openalex.org/W2886944874","https://openalex.org/W2963617879","https://openalex.org/W2963619659","https://openalex.org/W2991514044","https://openalex.org/W3004166074","https://openalex.org/W3109908659","https://openalex.org/W3127535616","https://openalex.org/W3159272845","https://openalex.org/W4211113486","https://openalex.org/W4214498907","https://openalex.org/W4226062951","https://openalex.org/W4226265017","https://openalex.org/W4297833479","https://openalex.org/W4309028162","https://openalex.org/W4312388571","https://openalex.org/W4312871721","https://openalex.org/W4312901297","https://openalex.org/W4322760572","https://openalex.org/W4386071550","https://openalex.org/W4386075599","https://openalex.org/W4386076114","https://openalex.org/W4386076290","https://openalex.org/W4389104737","https://openalex.org/W4402703035","https://openalex.org/W4402754131","https://openalex.org/W4402816534","https://openalex.org/W4402915803","https://openalex.org/W4404002617","https://openalex.org/W4405895842","https://openalex.org/W4407982277","https://openalex.org/W4410294774","https://openalex.org/W4413145021","https://openalex.org/W4413147880","https://openalex.org/W4413156589","https://openalex.org/W4413157275","https://openalex.org/W4415800744"],"related_works":[],"abstract_inverted_index":{"Stereo":[0],"matching":[1,53,85],"networks":[2],"can":[3],"suffer":[4],"from":[5,36],"generalization":[6,49],"challenges":[7],"when":[8],"trained":[9],"on":[10,22,122,139,146,153],"synthetic":[11,61],"data":[12,96],"and":[13,40,126,148],"deployed":[14],"in":[15,87,98,110,133],"real-world":[16,128],"settings.":[17],"While":[18],"existing":[19],"methods":[20],"rely":[21],"fine-tuning":[23],"or":[24,69],"pre-trained":[25],"vision":[26],"foundation":[27],"models":[28,54],"for":[29,166],"cross-domain":[30],"robustness,":[31,134],"we":[32,75,91,101,114],"revisit":[33],"this":[34],"gap":[35],"a":[37,42,57,82],"training":[38,44,164],"perspective":[39],"explore":[41],"structure-grounded":[43,163],"design":[45,165],"that":[46],"directly":[47],"improves":[48],"of":[50,60,81,162],"RNN-based":[51],"stereo":[52,62,84,169],"using":[55],"only":[56],"limited":[58],"amount":[59],"data,":[63],"without":[64],"changing":[65],"the":[66,158],"network":[67],"architecture":[68],"adding":[70],"any":[71],"inference":[72],"overhead.":[73],"Specifically,":[74],"target":[76],"all":[77],"three":[78],"main":[79],"modules":[80],"typical":[83],"pipeline:":[86],"cost":[88],"volume":[89],"construction,":[90],"enhance":[92],"geometric":[93],"cues":[94],"through":[95],"augmentation;":[97],"context":[99,108],"encoding,":[100],"strengthen":[102],"semantic":[103],"guidance":[104],"via":[105],"auxiliary":[106],"multitask":[107],"supervision;":[109],"recurrent":[111],"disparity":[112],"refinement,":[113],"regulate":[115],"update":[116],"dynamics":[117],"with":[118],"depth-update":[119],"regularization.":[120],"Experiments":[121],"multiple":[123],"mainstream":[124],"architectures":[125],"diverse":[127],"datasets":[129],"suggest":[130],"consistent":[131],"gains":[132],"improving":[135],"RAFT-Stereo":[136],"by":[137,143,150],"6.6%":[138],"KITTI":[140],"2015,":[141],"IGEV-Stereo":[142],"13.7":[144],"%":[145,152],"Middlebury,":[147],"DLNR":[149],"55.4":[151],"ETH3D.":[154],"These":[155],"insights":[156],"reveal":[157],"previously":[159],"overlooked":[160],"importance":[161],"achieving":[167],"reliable":[168],"depth":[170],"estimation":[171],"under":[172],"data-scarce,":[173],"domain-shifted":[174],"conditions.":[175]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-28T00:00:00"}