{"id":"https://openalex.org/W7147037026","doi":"https://doi.org/10.1109/icvisp68610.2025.11451726","title":"Robust Two-Stage Image Stitching via Multi-Scale Homography Regression","display_name":"Robust Two-Stage Image Stitching via Multi-Scale Homography Regression","publication_year":2025,"publication_date":"2025-11-28","ids":{"openalex":"https://openalex.org/W7147037026","doi":"https://doi.org/10.1109/icvisp68610.2025.11451726"},"language":null,"primary_location":{"id":"doi:10.1109/icvisp68610.2025.11451726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icvisp68610.2025.11451726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 9th International Conference on Vision, Image and Signal Processing (ICVISP)","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/A5132600301","display_name":"Yixing Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yixing Lv","raw_affiliation_strings":["Beijing Institute of Technology,School of Computer Science,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,School of Computer Science,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132646749","display_name":"Linwei Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linwei Chen","raw_affiliation_strings":["Beijing Institute of Technology,School of Information and Electronics,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,School of Information and Electronics,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132721751","display_name":"Ying Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Fu","raw_affiliation_strings":["Beijing Institute of Technology,School of Computer Science,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology,School of Computer Science,Beijing,China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132699506","display_name":"Hao Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Hu","raw_affiliation_strings":["China Mobile (Zhejiang) Innovation Research Institute Co., Ltd.,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"China Mobile (Zhejiang) Innovation Research Institute Co., Ltd.,Hangzhou,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132721472","display_name":"Jian Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Jiang","raw_affiliation_strings":["China Mobile (Zhejiang) Innovation Research Institute Co., Ltd.,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"China Mobile (Zhejiang) Innovation Research Institute Co., Ltd.,Hangzhou,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5132556272","display_name":"Chenggang Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenggang Yan","raw_affiliation_strings":["Hangzhou Dianzi University,School of Communication Engineering,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University,School of Communication Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5132600301"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.74850956,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9678999781608582,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9678999781608582,"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/T11448","display_name":"Face recognition and analysis","score":0.005799999926239252,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.0031999999191612005,"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/image-stitching","display_name":"Image stitching","score":0.9276999831199646},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5827000141143799},{"id":"https://openalex.org/keywords/homography","display_name":"Homography","score":0.5759000182151794},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5289999842643738},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46000000834465027},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.44339999556541443},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4293999969959259}],"concepts":[{"id":"https://openalex.org/C29081049","wikidata":"https://www.wikidata.org/wiki/Q1364242","display_name":"Image stitching","level":2,"score":0.9276999831199646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8632000088691711},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7548999786376953},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6643999814987183},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5827000141143799},{"id":"https://openalex.org/C28751775","wikidata":"https://www.wikidata.org/wiki/Q2112539","display_name":"Homography","level":4,"score":0.5759000182151794},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5289999842643738},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46000000834465027},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.44339999556541443},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.397599995136261},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3732999861240387},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.34459999203681946},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26589998602867126},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icvisp68610.2025.11451726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icvisp68610.2025.11451726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 9th International Conference on Vision, Image and Signal Processing (ICVISP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2085261163","https://openalex.org/W2151103935","https://openalex.org/W2963346260","https://openalex.org/W3013064625","https://openalex.org/W3034963870","https://openalex.org/W3042421830","https://openalex.org/W3095840465","https://openalex.org/W3138516171","https://openalex.org/W3175249881","https://openalex.org/W3186573928","https://openalex.org/W3189845786","https://openalex.org/W3214403471","https://openalex.org/W4200292189","https://openalex.org/W4249418251","https://openalex.org/W4297676427","https://openalex.org/W4378375546","https://openalex.org/W4387063747","https://openalex.org/W4390872094","https://openalex.org/W4390970172","https://openalex.org/W4392172931","https://openalex.org/W4393405457","https://openalex.org/W4396753393","https://openalex.org/W4400876843","https://openalex.org/W4400876846","https://openalex.org/W4401879614","https://openalex.org/W4407938696","https://openalex.org/W4411336874","https://openalex.org/W4412164112","https://openalex.org/W4412623660"],"related_works":[],"abstract_inverted_index":{"Image":[0],"stitching":[1,61,157],"is":[2],"a":[3,17,89,102],"widely":[4],"used":[5],"and":[6,53,116,138,155,161],"practical":[7],"computer":[8],"vision":[9],"technique,":[10],"which":[11],"aims":[12],"to":[13,56,112,133],"generate":[14],"images":[15],"with":[16],"wide":[18],"field":[19],"of":[20,31,81],"view.":[21],"Traditional":[22],"feature-based":[23],"methods":[24,62,158],"are":[25],"heavily":[26],"relying":[27],"on":[28],"the":[29,97,124],"quality":[30],"geometric":[32],"features,":[33],"often":[34],"showing":[35],"poor":[36],"performance":[37,167],"in":[38,49,78,142,168],"low-texture":[39],"scenarios.":[40],"Recently,":[41],"deep":[42,59,65],"learning-based":[43,60],"approaches":[44],"have":[45],"demonstrated":[46],"significant":[47],"advantages":[48],"feature":[50,70],"detection":[51],"capability":[52],"robustness.":[54],"Compared":[55],"traditional":[57],"methods,":[58],"adaptively":[63],"learn":[64,135],"semantic":[66],"features":[67,115],"through":[68,120],"powerful":[69],"extraction":[71],"networks,":[72],"but":[73],"they":[74],"still":[75],"face":[76],"challenges":[77],"handling":[79],"details":[80,170],"local":[82,169],"areas.":[83],"In":[84,96,123],"this":[85],"paper,":[86],"we":[87,100,127],"propose":[88],"two-stage":[90],"supervised":[91,103],"framework":[92],"for":[93],"image":[94,156],"stitching.":[95],"first":[98],"stage,":[99,126],"design":[101],"homography":[104,118,153],"network":[105],"that":[106,148],"employs":[107],"hybrid":[108],"attention":[109],"convolutional":[110],"layers":[111],"extract":[113],"multi-scale":[114],"predicts":[117],"transformations":[119],"multi-stage":[121],"regression.":[122],"second":[125],"designed":[128],"an":[129],"attention-feature":[130],"reconstruction":[131],"module":[132],"better":[134,166],"seam":[136],"information":[137],"eliminate":[139],"artifacts":[140],"present":[141],"coarse-aligned":[143],"images.":[144],"Experimental":[145],"results":[146],"demonstrate":[147],"our":[149],"approach":[150],"outperforms":[151],"existing":[152],"prediction":[154],"both":[159],"qualitatively":[160],"quantitatively,":[162],"while":[163],"also":[164],"show":[165],"processing.":[171]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-04-02T00:00:00"}
