{"id":"https://openalex.org/W3203786224","doi":"https://doi.org/10.5220/0011087800003209","title":"Using Keypoint Matching and Interactive Self Attention Network to Verify Retail POSMs","display_name":"Using Keypoint Matching and Interactive Self Attention Network to Verify Retail POSMs","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W3203786224","doi":"https://doi.org/10.5220/0011087800003209","mag":"3203786224"},"language":"en","primary_location":{"id":"doi:10.5220/0011087800003209","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0011087800003209","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Image Processing and Vision Engineering","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0011087800003209","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054693020","display_name":"Harshita Seth","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Harshita Seth","raw_affiliation_strings":["ParallelDots,Inc., India, --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"ParallelDots,Inc., India, --- Select a Country ---","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066269866","display_name":"Sonaal Kant","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sonaal Kant","raw_affiliation_strings":["ParallelDots,Inc., India, --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"ParallelDots,Inc., India, --- Select a Country ---","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107234012","display_name":"Muktabh Srivastava","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Muktabh Srivastava","raw_affiliation_strings":["ParallelDots,Inc., India, --- Select a Country ---"],"affiliations":[{"raw_affiliation_string":"ParallelDots,Inc., India, --- Select a Country ---","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054693020"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00372301,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"195","last_page":"201"},"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":0.9988999962806702,"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":0.9988999962806702,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9976000189781189,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9952999949455261,"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":0.7273277640342712},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6895449161529541},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5797673463821411},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.550915539264679},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5337271094322205},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.529001772403717},{"id":"https://openalex.org/keywords/point-of-sale","display_name":"Point of sale","score":0.5253814458847046},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4946756064891815},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45297306776046753},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4287317991256714},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4156906008720398},{"id":"https://openalex.org/keywords/stylized-fact","display_name":"Stylized fact","score":0.4106304943561554},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3405230939388275},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3375638425350189},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10460400581359863},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09853243827819824},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09447118639945984}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7273277640342712},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6895449161529541},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5797673463821411},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.550915539264679},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5337271094322205},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.529001772403717},{"id":"https://openalex.org/C58033187","wikidata":"https://www.wikidata.org/wiki/Q386147","display_name":"Point of sale","level":2,"score":0.5253814458847046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4946756064891815},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45297306776046753},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4287317991256714},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4156906008720398},{"id":"https://openalex.org/C38935604","wikidata":"https://www.wikidata.org/wiki/Q4330363","display_name":"Stylized fact","level":2,"score":0.4106304943561554},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3405230939388275},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3375638425350189},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10460400581359863},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09853243827819824},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09447118639945984},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0011087800003209","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0011087800003209","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Image Processing and Vision Engineering","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5220/0011087800003209","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0011087800003209","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Image Processing and Vision Engineering","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2117228865","https://openalex.org/W2440384215","https://openalex.org/W2560741668","https://openalex.org/W2892219791","https://openalex.org/W2963341956","https://openalex.org/W2963420686","https://openalex.org/W2964309429","https://openalex.org/W2970597249","https://openalex.org/W3092184047"],"related_works":["https://openalex.org/W2529311304","https://openalex.org/W4248275646","https://openalex.org/W2992609826","https://openalex.org/W3124809058","https://openalex.org/W2552900035","https://openalex.org/W2162875951","https://openalex.org/W2062875858","https://openalex.org/W4380047323","https://openalex.org/W2083539786","https://openalex.org/W2996462014"],"abstract_inverted_index":{"Point":[0],"of":[1,27,54,56,66,103,141],"Sale":[2],"Materials(POSM)":[3],"are":[4,11,25,33,69],"the":[5,52,101,113,120],"merchandising":[6],"and":[7,19,32,91,127,132],"decoration":[8],"items":[9],"that":[10,112],"used":[12],"by":[13,60,105],"companies":[14],"to":[15,51,87,99,119],"communicate":[16],"product":[17],"information":[18],"offers":[20],"in":[21,58,71],"retail":[22,29,41,142],"stores.":[23],"POSMs":[24,57],"part":[26],"companies'":[28],"marketing":[30],"strategy":[31],"often":[34],"applied":[35],"as":[36,84],"stylized":[37],"window":[38,67],"displays":[39],"around":[40],"shelves.":[42],"In":[43],"this":[44],"work,":[45],"we":[46],"apply":[47],"computer":[48],"vision":[49],"techniques":[50],"task":[53],"verification":[55],"supermarkets":[59],"telling":[61],"if":[62],"all":[63],"desired":[64],"components":[65,90],"display":[68],"present":[70],"a":[72,85,93,106,137],"shelf":[73,143],"image.":[74],"We":[75,109,130],"use":[76],"Convolutional":[77],"Neural":[78,95],"Network":[79,96],"based":[80,97],"unsupervised":[81],"keypoint":[82],"matching":[83],"baseline":[86,104],"verify":[88],"POSM":[89,121],"propose":[92],"supervised":[94,114],"method":[98],"enhance":[100],"accuracy":[102],"large":[107],"margin.":[108],"also":[110],"show":[111],"pipeline":[115],"is":[116,124],"not":[117],"restricted":[118],"material":[122],"it":[123],"trained":[125],"on":[126,136],"can":[128],"generalize.":[129],"train":[131],"evaluate":[133],"our":[134],"model":[135],"private":[138],"dataset":[139],"composed":[140],"images.":[144]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}