{"id":"https://openalex.org/W4403636392","doi":"https://doi.org/10.1145/3681769.3698582","title":"Random Affine Transformation Feature Representation Learning for Fast Polygon Retrieval","display_name":"Random Affine Transformation Feature Representation Learning for Fast Polygon Retrieval","publication_year":2024,"publication_date":"2024-10-22","ids":{"openalex":"https://openalex.org/W4403636392","doi":"https://doi.org/10.1145/3681769.3698582"},"language":"en","primary_location":{"id":"doi:10.1145/3681769.3698582","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3681769.3698582","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3681769.3698582","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047265807","display_name":"Zhangyu Wang","orcid":"https://orcid.org/0009-0004-4728-4458"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhangyu Wang","raw_affiliation_strings":["University of California Santa Barbara, United States"],"raw_orcid":"https://orcid.org/0009-0004-4728-4458","affiliations":[{"raw_affiliation_string":"University of California Santa Barbara, United States","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048512014","display_name":"Xingyi Du","orcid":"https://orcid.org/0000-0001-6036-6782"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xingyi Du","raw_affiliation_strings":["Tencent, United States"],"raw_orcid":"https://orcid.org/0000-0001-6036-6782","affiliations":[{"raw_affiliation_string":"Tencent, United States","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348619","display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-6336-8772"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["Technical University of Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0002-6336-8772","affiliations":[{"raw_affiliation_string":"Technical University of Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062987908","display_name":"Martin Werner","orcid":"https://orcid.org/0000-0002-6951-8022"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Werner","raw_affiliation_strings":["Technical University of Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0002-6951-8022","affiliations":[{"raw_affiliation_string":"Technical University of Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5047265807"],"corresponding_institution_ids":["https://openalex.org/I154570441"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1756958,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"22","last_page":"28"},"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":0.9993000030517578,"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":0.9993000030517578,"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/T10824","display_name":"Image Retrieval and Classification 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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9933000206947327,"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/affine-transformation","display_name":"Affine transformation","score":0.7867001295089722},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.707667350769043},{"id":"https://openalex.org/keywords/polygon","display_name":"Polygon (computer graphics)","score":0.6706137657165527},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6391650438308716},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.636629581451416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5454370379447937},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.539910078048706},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40990573167800903},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3707174062728882},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21067765355110168},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.06302279233932495}],"concepts":[{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.7867001295089722},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.707667350769043},{"id":"https://openalex.org/C190694206","wikidata":"https://www.wikidata.org/wiki/Q3276654","display_name":"Polygon (computer graphics)","level":3,"score":0.6706137657165527},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6391650438308716},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.636629581451416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5454370379447937},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.539910078048706},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40990573167800903},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3707174062728882},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21067765355110168},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.06302279233932495},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3681769.3698582","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3681769.3698582","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3681769.3698582","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3681769.3698582","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2003612343","https://openalex.org/W2039530979","https://openalex.org/W2121157037","https://openalex.org/W2163922914","https://openalex.org/W2525627531","https://openalex.org/W2597187707","https://openalex.org/W2969656782","https://openalex.org/W3025159219","https://openalex.org/W4307085104","https://openalex.org/W4384010587","https://openalex.org/W4390100354"],"related_works":["https://openalex.org/W4380153838","https://openalex.org/W4398681136","https://openalex.org/W2383204375","https://openalex.org/W2107908243","https://openalex.org/W2038416447","https://openalex.org/W2364151838","https://openalex.org/W2000428152","https://openalex.org/W2066926363","https://openalex.org/W4398470586","https://openalex.org/W2765965840"],"abstract_inverted_index":{"Despite":[0],"the":[1,47,58,94,100,104,150,170,177],"advance":[2],"of":[3,7,22,50,106,173,181],"representation":[4,21,73],"learning":[5,74],"(RL)":[6],"image":[8],"and":[9,29,161,175,179],"text":[10],"data,":[11,78],"it":[12],"is":[13],"a":[14,19,52,62,71,133],"challenging":[15],"task":[16],"to":[17,112,145,168],"obtain":[18],"general-purpose":[20],"vector-based":[23],"spatial":[24,37],"data":[25],"(e.g.,":[26],"point,":[27],"polyline,":[28],"polygon)":[30],"that":[31,130],"fulfills":[32],"domain-specific":[33],"prerequisites":[34],"in":[35,99],"downstream":[36],"analysis.":[38],"Towards":[39],"filling":[40],"this":[41,67],"gap,":[42],"we":[43,69],"put":[44],"focus":[45],"on":[46,93],"first":[48],"step":[49],"revisiting":[51],"classic":[53],"computational":[54],"geometry":[55],"task,":[56],"namely":[57,79],"polygon":[59,77,141],"retrieval,":[60],"with":[61],"modern":[63],"RL":[64],"approach.":[65],"In":[66],"paper,":[68],"propose":[70],"novel":[72],"method":[75],"for":[76,187],"Random":[80,87],"Affine":[81],"Transformation":[82],"Features":[83],"(RATFs).":[84],"Inspired":[85],"by":[86,131],"Fourier":[88],"Features,":[89],"RATFs":[90,174],"represent":[91],"polygons":[92,118,148],"plane":[95],"into":[96,123],"vector":[97],"embeddings":[98,142],"high-dimensional":[101],"space":[102],"using":[103,132],"basis":[105],"random":[107],"anchor":[108],"polygons,":[109],"allowing":[110],"us":[111],"transform":[113],"complex,":[114],"non-batch-wise":[115],"computations":[116],"between":[117],"such":[119],"as":[120],"Hausdorff":[121,157],"distance":[122],"simple,":[124],"batch-wise":[125],"inner":[126],"products.":[127],"Experiments":[128],"demonstrate":[129,169],"naive":[134],"3-layer":[135],"feed-forward":[136],"network,":[137],"our":[138],"RATFs-based":[139,184],"neural":[140,185],"are":[143],"able":[144],"retrieve":[146],"similar":[147],"from":[149],"corpus":[151],"100,000":[152],"times":[153],"faster":[154],"than":[155],"computing":[156],"distances":[158],"at":[159],"inferencing":[160],"achieve":[162],"good":[163],"retrieval":[164],"quality.":[165],"We":[166],"aim":[167],"representational":[171],"power":[172],"leave":[176],"design":[178],"tuning":[180],"more":[182],"advanced":[183],"networks":[186],"future":[188],"work.":[189]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}