{"id":"https://openalex.org/W2963346492","doi":"https://doi.org/10.1109/icra.2017.7989197","title":"Learning social affordance grammar from videos: Transferring human interactions to human-robot interactions","display_name":"Learning social affordance grammar from videos: Transferring human interactions to human-robot interactions","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2963346492","doi":"https://doi.org/10.1109/icra.2017.7989197","mag":"2963346492"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2017.7989197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2017.7989197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5005908625","display_name":"Tianmin Shu","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianmin Shu","raw_affiliation_strings":["Center for Vision, Cogntion, Learning, and Autonomy, University of California, Los Angeles, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Vision, Cogntion, Learning, and Autonomy, University of California, Los Angeles, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023073132","display_name":"Xiaofeng Gao","orcid":"https://orcid.org/0000-0003-3331-9846"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofeng Gao","raw_affiliation_strings":["Department of Electronic Engineering, Fudan University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084829008","display_name":"Michael S. Ryoo","orcid":"https://orcid.org/0000-0002-5452-8332"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael S. Ryoo","raw_affiliation_strings":["School of Informatics and Computing, Indiana University, Bloomington, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics and Computing, Indiana University, Bloomington, USA","institution_ids":["https://openalex.org/I4210119109"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034228010","display_name":"Song\u2010Chun Zhu","orcid":"https://orcid.org/0000-0002-1925-5973"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Song-Chun Zhu","raw_affiliation_strings":["Center for Vision, Cogntion, Learning, and Autonomy, University of California, Los Angeles, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Vision, Cogntion, Learning, and Autonomy, University of California, Los Angeles, USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1669","last_page":"1676"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9987000226974487,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7889213562011719},{"id":"https://openalex.org/keywords/affordance","display_name":"Affordance","score":0.7619192600250244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6654950380325317},{"id":"https://openalex.org/keywords/grammar","display_name":"Grammar","score":0.5428649187088013},{"id":"https://openalex.org/keywords/human\u2013robot-interaction","display_name":"Human\u2013robot interaction","score":0.542064905166626},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5295442342758179},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4467153251171112},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4375322163105011},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.42469996213912964},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41825246810913086},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4098353981971741},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.12958580255508423}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7889213562011719},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.7619192600250244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6654950380325317},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.5428649187088013},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.542064905166626},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5295442342758179},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4467153251171112},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4375322163105011},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.42469996213912964},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41825246810913086},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4098353981971741},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.12958580255508423},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2017.7989197","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2017.7989197","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W276494664","https://openalex.org/W1613163714","https://openalex.org/W1891689858","https://openalex.org/W1907587592","https://openalex.org/W1920293286","https://openalex.org/W1933657216","https://openalex.org/W1969652666","https://openalex.org/W1972696612","https://openalex.org/W2003708924","https://openalex.org/W2028798328","https://openalex.org/W2032293070","https://openalex.org/W2047499569","https://openalex.org/W2058256495","https://openalex.org/W2061017280","https://openalex.org/W2112913186","https://openalex.org/W2115815548","https://openalex.org/W2116137332","https://openalex.org/W2137275576","https://openalex.org/W2139117248","https://openalex.org/W2141664020","https://openalex.org/W2149173366","https://openalex.org/W2155217025","https://openalex.org/W2171544105","https://openalex.org/W2185953016","https://openalex.org/W2269938945","https://openalex.org/W2304253768","https://openalex.org/W2414920489","https://openalex.org/W2416663518","https://openalex.org/W2499741433","https://openalex.org/W2963738870","https://openalex.org/W6639622275","https://openalex.org/W6677531546","https://openalex.org/W6712333017"],"related_works":["https://openalex.org/W1972718289","https://openalex.org/W1791514435","https://openalex.org/W2346831895","https://openalex.org/W2248634132","https://openalex.org/W2295809616","https://openalex.org/W3049116993","https://openalex.org/W2070708245","https://openalex.org/W1541884709","https://openalex.org/W2589081601","https://openalex.org/W1966542732"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,14,33,53,76],"general":[6],"framework":[7],"for":[8,37],"learning":[9,49],"social":[10],"affordance":[11],"grammar":[12,28,48],"as":[13],"spatiotemporal":[15],"AND-OR":[16],"graph":[17],"(ST-AOG)":[18],"from":[19,103],"RGB-D":[20,78],"videos":[21],"of":[22,56,63,71,84,89],"human":[23,85,92],"interactions,":[24,86],"and":[25,66,94,114],"transfer":[26],"the":[27,100],"to":[29,31],"humanoids":[30],"enable":[32],"real-time":[34],"motion":[35],"inference":[36],"human-robot":[38],"interaction":[39,58],"(HRI).":[40],"Based":[41,74],"on":[42,75],"Gibbs":[43],"sampling,":[44],"our":[45,87],"weakly":[46],"supervised":[47],"can":[50],"automatically":[51],"construct":[52],"hierarchical":[54],"representation":[55],"an":[57],"with":[59,81],"long-term":[60],"joint":[61],"sub-tasks":[62],"both":[64,116],"agents":[65],"short":[67],"term":[68],"atomic":[69],"actions":[70],"individual":[72],"agents.":[73],"new":[77],"video":[79],"dataset":[80],"rich":[82],"instances":[83],"experiments":[88],"Baxter":[90,96],"simulation,":[91],"evaluation,":[93],"real":[95],"test":[97],"demonstrate":[98],"that":[99],"model":[101],"learned":[102],"limited":[104],"training":[105],"data":[106],"successfully":[107],"generates":[108],"human-like":[109],"behaviors":[110],"in":[111],"unseen":[112],"scenarios":[113],"outperforms":[115],"baselines.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
