{"id":"https://openalex.org/W4383108738","doi":"https://doi.org/10.1109/icra48891.2023.10160863","title":"Deep Interactive Full Transformer Framework for Point Cloud Registration","display_name":"Deep Interactive Full Transformer Framework for Point Cloud Registration","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383108738","doi":"https://doi.org/10.1109/icra48891.2023.10160863"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10160863","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra48891.2023.10160863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5070438520","display_name":"Guangyan Chen","orcid":"https://orcid.org/0000-0002-4592-4253"},"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":"Guangyan Chen","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology,Beijing,China,100081"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology,Beijing,China,100081","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100416064","display_name":"Meiling Wang","orcid":"https://orcid.org/0000-0002-3618-7423"},"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":"Meiling Wang","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology,Beijing,China,100081"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology,Beijing,China,100081","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016187481","display_name":"Qingxiang Zhang","orcid":"https://orcid.org/0000-0003-0294-7647"},"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":"Qingxiang Zhang","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology,Beijing,China,100081"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology,Beijing,China,100081","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101841378","display_name":"Yuan Li","orcid":"https://orcid.org/0000-0001-5266-3373"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Yuan","raw_affiliation_strings":["School of Electrical and Computer Engineering at Peking University,Pecheng Lab,Shenzhen,China,518055"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering at Peking University,Pecheng Lab,Shenzhen,China,518055","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100392682","display_name":"Tong Liu","orcid":"https://orcid.org/0000-0003-0686-3846"},"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":"Tong Liu","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology,Beijing,China,100081"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology,Beijing,China,100081","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068949782","display_name":"Yufeng Yue","orcid":"https://orcid.org/0000-0001-6628-7946"},"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":"Yufeng Yue","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology,Beijing,China,100081"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology,Beijing,China,100081","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8693,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.90359026,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9991999864578247,"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":0.9991999864578247,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9933000206947327,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.83912593126297},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7983068227767944},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6767414808273315},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5381612777709961},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5275048017501831},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4730730950832367},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4712643623352051},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.46092793345451355},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44225701689720154},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37053585052490234},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3510475158691406},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.096316397190094}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.83912593126297},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7983068227767944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6767414808273315},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5381612777709961},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5275048017501831},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4730730950832367},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4712643623352051},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.46092793345451355},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44225701689720154},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37053585052490234},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3510475158691406},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.096316397190094},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10160863","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra48891.2023.10160863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.4399999976158142,"display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G2459129960","display_name":null,"funder_award_id":"62003039,62233002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"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":58,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1920022804","https://openalex.org/W1990283121","https://openalex.org/W2049981393","https://openalex.org/W2118877769","https://openalex.org/W2187089797","https://openalex.org/W2469169366","https://openalex.org/W2560609797","https://openalex.org/W2566265240","https://openalex.org/W2612690371","https://openalex.org/W2618530766","https://openalex.org/W2752782242","https://openalex.org/W2889895098","https://openalex.org/W2896457183","https://openalex.org/W2963264709","https://openalex.org/W2964014140","https://openalex.org/W2981685844","https://openalex.org/W2981689412","https://openalex.org/W2981995220","https://openalex.org/W2986382673","https://openalex.org/W3013243617","https://openalex.org/W3030520226","https://openalex.org/W3034675048","https://openalex.org/W3035030518","https://openalex.org/W3035338950","https://openalex.org/W3080980548","https://openalex.org/W3096538374","https://openalex.org/W3097065222","https://openalex.org/W3108059345","https://openalex.org/W3121523901","https://openalex.org/W3133797311","https://openalex.org/W3166855724","https://openalex.org/W3177280664","https://openalex.org/W3179449781","https://openalex.org/W3183233802","https://openalex.org/W3195006234","https://openalex.org/W3203699830","https://openalex.org/W3212992486","https://openalex.org/W3214555988","https://openalex.org/W3216353509","https://openalex.org/W4214755140","https://openalex.org/W4220967590","https://openalex.org/W4221160436","https://openalex.org/W4221160556","https://openalex.org/W4292779060","https://openalex.org/W4295308583","https://openalex.org/W4298395628","https://openalex.org/W4312516208","https://openalex.org/W6631190155","https://openalex.org/W6640300118","https://openalex.org/W6662860747","https://openalex.org/W6755207826","https://openalex.org/W6763367864","https://openalex.org/W6763422710","https://openalex.org/W6767019538","https://openalex.org/W6778485988","https://openalex.org/W6778883912","https://openalex.org/W6802758728"],"related_works":["https://openalex.org/W3016928466","https://openalex.org/W4293226380","https://openalex.org/W4389574804","https://openalex.org/W2123263858","https://openalex.org/W3127959533","https://openalex.org/W2936725271","https://openalex.org/W3150655618","https://openalex.org/W2295788148","https://openalex.org/W4320086129","https://openalex.org/W2950785639"],"abstract_inverted_index":{"Point":[0,131,146],"cloud":[1,21,121],"registration":[2,22],"is":[3,205],"a":[4,78,130,145,164],"crucial":[5],"technology":[6],"in":[7,19,64],"the":[8,16,46,71,94,112,157,188],"fields":[9],"of":[10,48,74,80,96,103,125,191],"robotics":[11],"and":[12,36,88,92,140,154,162,176,184],"computer":[13],"vision.":[14],"Despite":[15],"significant":[17],"advances":[18],"point":[20,120],"enabled":[23],"by":[24],"Transformer-based":[25],"methods,":[26],"limitations":[27,40],"persist":[28],"due":[29,57],"to":[30,53,58,68,84,100,196],"indistinct":[31,89],"feature":[32,90],"extraction,":[33],"noise":[34],"sensitivity,":[35],"outlier":[37],"handling.":[38],"These":[39],"stem":[41],"from":[42],"three":[43,126],"factors:":[44],"(1)":[45,129],"inefficiency":[47],"convolutional":[49],"neural":[50],"networks":[51],"(CNNs)":[52],"capture":[54],"global":[55,138],"relationships":[56,139],"their":[59],"local":[60],"receptive":[61],"fields,":[62],"resulting":[63],"extracted":[65],"features":[66],"susceptible":[67],"noise;":[69],"(2)":[70,144],"shallow-wide":[72],"architecture":[73],"Transformers,":[75],"coupled":[76],"with":[77],"lack":[79],"positional":[81],"information,":[82],"leading":[83],"inefficient":[85],"information":[86],"interaction":[87],"extraction;":[91],"(3)":[93,163],"omission":[95],"geometrical":[97],"compatibility":[98],"leads":[99],"ambiguous":[101],"identification":[102],"incorrect":[104],"correspondences.":[105],"To":[106],"overcome":[107],"these":[108],"limitations,":[109],"we":[110],"propose":[111],"Deep":[113],"Interactive":[114],"Full":[115],"Transformer":[116,148],"(DIFT)":[117],"network":[118],"for":[119,136,150,172,202],"registration,":[122],"which":[123],"consists":[124],"key":[127],"components:":[128],"Cloud":[132],"Structure":[133],"Extractor":[134],"(PSE)":[135],"modeling":[137],"retrieving":[141],"structural":[142],"information;":[143],"Feature":[147],"(PFT)":[149],"establishing":[151],"comprehensive":[152],"associations":[153],"directly":[155],"learning":[156],"relative":[158],"positions":[159],"between":[160],"points;":[161],"Geometric":[165],"Matching-based":[166],"Correspondence":[167],"Confidence":[168],"Evaluation":[169],"(GMCCE)":[170],"method":[171,194,204],"measuring":[173],"spatial":[174],"consistency":[175],"estimating":[177],"correspondence":[178],"confidence.":[179],"Experimental":[180],"results":[181],"on":[182],"ModelNet40":[183],"3DMatch":[185],"datasets":[186],"demonstrate":[187],"superior":[189],"performance":[190],"our":[192,203],"proposed":[193],"compared":[195],"existing":[197],"state-of-the-art":[198],"methods.":[199],"The":[200],"code":[201],"publicly":[206],"available":[207],"at":[208],"https://github.com/CGuangyan-BIT/DIFT.":[209]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
