{"id":"https://openalex.org/W4383108370","doi":"https://doi.org/10.1109/icra48891.2023.10160666","title":"NIFT: Neural Interaction Field and Template for Object Manipulation","display_name":"NIFT: Neural Interaction Field and Template for Object Manipulation","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383108370","doi":"https://doi.org/10.1109/icra48891.2023.10160666"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10160666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160666","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":"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/A5101432063","display_name":"Zeyu Huang","orcid":"https://orcid.org/0000-0002-0456-8379"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zeyu Huang","raw_affiliation_strings":["Shenzhen University"],"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051130170","display_name":"Juzhan Xu","orcid":"https://orcid.org/0000-0002-5132-238X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juzhan Xu","raw_affiliation_strings":["Shenzhen University"],"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102741636","display_name":"Sisi Dai","orcid":"https://orcid.org/0000-0002-8262-8138"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sisi Dai","raw_affiliation_strings":["National University of Defense Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000248352","display_name":"Kai Xu","orcid":"https://orcid.org/0000-0002-9054-0216"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Xu","raw_affiliation_strings":["National University of Defense Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100397026","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0003-1991-119X"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["Simon Fraser University"],"affiliations":[{"raw_affiliation_string":"Simon Fraser University","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034304352","display_name":"Hui Huang","orcid":"https://orcid.org/0000-0003-3212-0544"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Huang","raw_affiliation_strings":["Shenzhen University"],"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013892799","display_name":"Ruizhen Hu","orcid":"https://orcid.org/0000-0002-6798-0336"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruizhen Hu","raw_affiliation_strings":["Shenzhen University"],"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101432063"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":1.8761,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.85423473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1875","last_page":"1881"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10812","display_name":"Human Pose and Action Recognition","score":0.9980000257492065,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9815000295639038,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.7110834717750549},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6729205250740051},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.614996612071991},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5541431903839111},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5147712230682373},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.49014243483543396},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.4880789518356323},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4740585684776306},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4402189552783966},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.41877374053001404},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.41030603647232056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39759528636932373},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18542402982711792}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7110834717750549},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6729205250740051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.614996612071991},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5541431903839111},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5147712230682373},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.49014243483543396},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.4880789518356323},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4740585684776306},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4402189552783966},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.41877374053001404},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.41030603647232056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39759528636932373},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18542402982711792},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10160666","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160666","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G1256189497","display_name":null,"funder_award_id":"U2001206,U21B2023,62132021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5157693904","display_name":null,"funder_award_id":"611370","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G8571217899","display_name":null,"funder_award_id":"RCYX20210609103121030","funder_id":"https://openalex.org/F4320326705","funder_display_name":"Science, Technology and Innovation Commission of Shenzhen Municipality"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326705","display_name":"Science, Technology and Innovation Commission of Shenzhen Municipality","ror":null},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W846029135","https://openalex.org/W1521162839","https://openalex.org/W1522301498","https://openalex.org/W1561952261","https://openalex.org/W1968630691","https://openalex.org/W1985473518","https://openalex.org/W1986014385","https://openalex.org/W2011792403","https://openalex.org/W2017279084","https://openalex.org/W2043690242","https://openalex.org/W2044032519","https://openalex.org/W2093271548","https://openalex.org/W2134236847","https://openalex.org/W2155182058","https://openalex.org/W2167730089","https://openalex.org/W2210993424","https://openalex.org/W2465056104","https://openalex.org/W2472053385","https://openalex.org/W2550600634","https://openalex.org/W2802065399","https://openalex.org/W2811406147","https://openalex.org/W2911024290","https://openalex.org/W2949233999","https://openalex.org/W2962849139","https://openalex.org/W2963166883","https://openalex.org/W2963627347","https://openalex.org/W2969694596","https://openalex.org/W2990974996","https://openalex.org/W3036642894","https://openalex.org/W3037767967","https://openalex.org/W3090004508","https://openalex.org/W3102270810","https://openalex.org/W3158545781","https://openalex.org/W3206191420","https://openalex.org/W3207755626","https://openalex.org/W4225319149","https://openalex.org/W4285102336","https://openalex.org/W4394671432","https://openalex.org/W6631190155","https://openalex.org/W6633448084","https://openalex.org/W6654714828","https://openalex.org/W6687484953","https://openalex.org/W6752823625","https://openalex.org/W6766850847","https://openalex.org/W6797287471","https://openalex.org/W6810644734"],"related_works":["https://openalex.org/W2140020064","https://openalex.org/W143502885","https://openalex.org/W2114275278","https://openalex.org/W2769899322","https://openalex.org/W1489511283","https://openalex.org/W2026565050","https://openalex.org/W2974914859","https://openalex.org/W2110244802","https://openalex.org/W949345935","https://openalex.org/W2060811007"],"abstract_inverted_index":{"We":[0],"introduce":[1],"NIFT,":[2],"Neural":[3,43,54],"Interaction":[4,44,55,146],"Field":[5,56],"and":[6,10,78,162,174,226],"Template,":[7],"a":[8,22,36,67,79,89,111,121],"descriptive":[9],"robust":[11],"interaction":[12,33,168,180],"representation":[13],"of":[14,31,123,152,191],"object":[15,24,38,194,224],"manipulations":[16],"to":[17,157,203,229],"facilitate":[18],"imitation":[19,34,220],"learning.":[20],"Given":[21],"few":[23],"manipulation":[25,206,225],"demos,":[26],"NIFT":[27,216],"guides":[28,184],"the":[29,32,42,49,52,60,64,72,83,115,128,138,140,145,158,185,189,192,198,205,209],"generation":[30],"for":[35,59,167,178,223],"new":[37,61,193,232],"instance":[39],"by":[40,88,103,120],"matching":[41,187],"Template":[45],"(NIT)":[46],"extracted":[47],"from":[48,231],"demos":[50],"in":[51,127,188],"target":[53],"(NIF)":[57],"defined":[58,87,119,177],"object.":[62],"Specifically,":[63],"NIF":[65,130],"is":[66,86,118],"neural":[68,105,133],"field":[69],"that":[70,154,197,214],"encodes":[71],"relationship":[73],"between":[74],"each":[75],"spatial":[76,124],"point":[77,172],"given":[80,112],"object,":[81],"where":[82],"relative":[84,199],"position":[85],"spherical":[90],"distance":[91],"function":[92],"rather":[93],"than":[94],"occupancies":[95],"or":[96],"signed":[97],"distances,":[98],"which":[99,150],"are":[100,142,155,201],"commonly":[101],"adopted":[102],"conventional":[104],"fields":[106],"but":[107],"less":[108],"informative.":[109],"For":[110],"demo":[113,129,210],"interaction,":[114,139],"corresponding":[116],"NIT":[117,182],"set":[122],"points":[125,141,153],"sampled":[126,143],"with":[131],"associated":[132],"features.":[134],"To":[135],"better":[136,179,228],"capture":[137],"on":[144],"Bisector":[147],"Surface":[148],"(IBS),":[149],"consists":[151],"equidistant":[156],"two":[159],"interacting":[160],"objects":[161,230],"has":[163],"been":[164],"used":[165],"extensively":[166],"representation.":[169],"With":[170],"both":[171],"selection":[173],"pointwise":[175],"features":[176],"encoding,":[181],"effectively":[183],"feature":[186],"NIFs":[190],"instances":[195],"such":[196],"poses":[200],"optimized":[202],"realize":[204],"while":[207],"imitating":[208],"interactions.":[211],"Experiments":[212],"show":[213],"our":[215],"solution":[217],"outperforms":[218],"state-of-the-art":[219],"learning":[221],"methods":[222],"generalizes":[227],"categories.":[233]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}