{"id":"https://openalex.org/W3034657620","doi":"https://doi.org/10.1109/icme46284.2020.9102925","title":"Cross-Modal Guidance Network For Sketch-Based 3d Shape Retrieval","display_name":"Cross-Modal Guidance Network For Sketch-Based 3d Shape Retrieval","publication_year":2020,"publication_date":"2020-06-09","ids":{"openalex":"https://openalex.org/W3034657620","doi":"https://doi.org/10.1109/icme46284.2020.9102925","mag":"3034657620"},"language":"en","primary_location":{"id":"doi:10.1109/icme46284.2020.9102925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","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/A5037232216","display_name":"Weidong Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weidong Dai","raw_affiliation_strings":["School of Software Engineering, Tongji University, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043630267","display_name":"Shuang Liang","orcid":"https://orcid.org/0000-0003-0457-6093"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Liang","raw_affiliation_strings":["School of Software Engineering, Tongji University, China"],"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Tongji University, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5037232216"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":1.5845,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.80326072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9921000003814697,"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/sketch","display_name":"Sketch","score":0.8803926706314087},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7568131685256958},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7552208304405212},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.7419332265853882},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7128838300704956},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6828451752662659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6367039084434509},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5458768010139465},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5185271501541138},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.5033578276634216},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4406718611717224},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3248663544654846},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11056283116340637}],"concepts":[{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.8803926706314087},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7568131685256958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7552208304405212},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7419332265853882},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7128838300704956},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6828451752662659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6367039084434509},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5458768010139465},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5185271501541138},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.5033578276634216},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4406718611717224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3248663544654846},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11056283116340637},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme46284.2020.9102925","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102925","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W295048775","https://openalex.org/W1644641054","https://openalex.org/W1686810756","https://openalex.org/W1821462560","https://openalex.org/W1892078565","https://openalex.org/W2005681003","https://openalex.org/W2049716301","https://openalex.org/W2099789128","https://openalex.org/W2157364932","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2259866506","https://openalex.org/W2294370754","https://openalex.org/W2529895177","https://openalex.org/W2561238782","https://openalex.org/W2604164738","https://openalex.org/W2748787960","https://openalex.org/W2749056374","https://openalex.org/W2784163702","https://openalex.org/W2791376837","https://openalex.org/W2810981979","https://openalex.org/W2962916234","https://openalex.org/W2963468606","https://openalex.org/W2963744743","https://openalex.org/W3103152812","https://openalex.org/W6637373629","https://openalex.org/W6638523607","https://openalex.org/W6684191040","https://openalex.org/W6728165149","https://openalex.org/W6730179637","https://openalex.org/W6735945695","https://openalex.org/W6740745780","https://openalex.org/W6743139828"],"related_works":["https://openalex.org/W2378994405","https://openalex.org/W2385974820","https://openalex.org/W2373478030","https://openalex.org/W2378679551","https://openalex.org/W3149739944","https://openalex.org/W2392363776","https://openalex.org/W2063051341","https://openalex.org/W2591066345","https://openalex.org/W156213964","https://openalex.org/W2050960118"],"abstract_inverted_index":{"The":[0],"main":[1],"challenge":[2],"of":[3,85,102],"sketch-based":[4],"3D":[5,17,86,120],"shape":[6],"retrieval":[7,135],"is":[8],"the":[9,33,47,82,89,99,109,118,138],"large":[10],"cross-modal":[11,48,68,110],"differences":[12,49],"between":[13],"2D":[14,103,112],"sketches":[15],"and":[16,26],"shapes.":[18,87],"Most":[19],"recent":[20],"works":[21],"employed":[22],"two":[23,126],"heterogeneous":[24],"networks":[25],"a":[27,39,56,61,77,95],"shared":[28],"loss":[29],"to":[30,38,45,64,80,97,107,117],"directly":[31],"map":[32],"features":[34,84,91,114],"from":[35],"different":[36],"modalities":[37],"common":[40],"feature":[41,69,100,121],"space,":[42],"which":[43],"failed":[44],"reduce":[46],"effectively.":[50],"In":[51,105],"this":[52],"paper,":[53],"we":[54],"propose":[55],"novel":[57],"method":[58,74,132],"that":[59,130],"adopts":[60],"teacher-student":[62],"strategy":[63],"learn":[65,81],"an":[66],"aligned":[67],"space":[70],"indirectly.":[71],"Specifically,":[72],"our":[73,131],"first":[75],"employs":[76],"classification":[78],"network":[79],"discriminative":[83],"Then,":[88],"pre-learned":[90,119],"are":[92,115],"considered":[93],"as":[94],"teacher":[96],"guide":[98],"learning":[101],"sketches.":[104],"order":[106],"align":[108],"features,":[111],"sketch":[113],"transferred":[116],"space.":[122],"Our":[123],"experiments":[124],"on":[125],"benchmark":[127],"datasets":[128],"demonstrate":[129],"obtains":[133],"superior":[134],"performance":[136],"than":[137],"state-of-the-art":[139],"approaches.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
