{"id":"https://openalex.org/W3096057444","doi":"https://doi.org/10.1145/3394171.3413778","title":"LIGHTEN","display_name":"LIGHTEN","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3096057444","doi":"https://doi.org/10.1145/3394171.3413778","mag":"3096057444"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413778","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2012.09402","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sai Praneeth Reddy Sunkesula","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sai Praneeth Reddy Sunkesula","raw_affiliation_strings":["Indian Institute of Technology, Bombay, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rishabh Dabral","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rishabh Dabral","raw_affiliation_strings":["Indian Institute of Technology, Bombay, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ganesh Ramakrishnan","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ganesh Ramakrishnan","raw_affiliation_strings":["Indian Institute of Technology, Bombay, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162827531"],"apc_list":null,"apc_paid":null,"fwci":1.5693,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.8585504,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"691","last_page":"699"},"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":0.9994000196456909,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980999827384949,"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/generalization","display_name":"Generalization","score":0.5317000150680542},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.48100000619888306},{"id":"https://openalex.org/keywords/human-visual-system-model","display_name":"Human visual system model","score":0.44190001487731934},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4235000014305115},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.41839998960494995},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4090000092983246},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4090000092983246},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4018999934196472}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7099999785423279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6657999753952026},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5317000150680542},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.48100000619888306},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45210000872612},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.44190001487731934},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4235000014305115},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4090000092983246},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4090000092983246},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4018999934196472},{"id":"https://openalex.org/C176777502","wikidata":"https://www.wikidata.org/wiki/Q4774623","display_name":"Anticipation (artificial intelligence)","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37059998512268066},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.27889999747276306},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3394171.3413778","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2012.09402","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.09402","pdf_url":"https://arxiv.org/pdf/2012.09402","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2012.09402","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.09402","pdf_url":"https://arxiv.org/pdf/2012.09402","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1483019628","https://openalex.org/W1559169059","https://openalex.org/W2146055337","https://openalex.org/W2301022680","https://openalex.org/W2307770531","https://openalex.org/W2576289912","https://openalex.org/W2765137706","https://openalex.org/W2788627475","https://openalex.org/W2809890486","https://openalex.org/W2883363148","https://openalex.org/W2948058585","https://openalex.org/W2951323451","https://openalex.org/W2955882737","https://openalex.org/W2962754033","https://openalex.org/W2963097937","https://openalex.org/W2963165299","https://openalex.org/W2963530216","https://openalex.org/W2963876278","https://openalex.org/W2963995996","https://openalex.org/W2981385984","https://openalex.org/W2981895973","https://openalex.org/W2982441354","https://openalex.org/W2982480216","https://openalex.org/W3009811369","https://openalex.org/W3034520808","https://openalex.org/W3034556939","https://openalex.org/W3034712684","https://openalex.org/W3034999503","https://openalex.org/W3035225512","https://openalex.org/W3035668851"],"related_works":[],"abstract_inverted_index":{"Analyzing":[0],"the":[1,13,18,22,40,50,108,112,117],"interactions":[2],"between":[3,15],"humans":[4,16],"and":[5,17,132,134,139],"objects":[6,19,41],"from":[7],"a":[8,30,44,55,62,79,151],"video":[9,58],"includes":[10],"identification":[11],"of":[12,28,33,39,57,116,137],"relationships":[14],"present":[20,61],"in":[21,78,127,147],"video.":[23,80],"It":[24],"can":[25],"be":[26,43],"thought":[27],"as":[29,52,103],"specialized":[31],"version":[32],"Visual":[34],"Relationship":[35],"Detection,":[36],"wherein":[37],"one":[38],"must":[42],"human.":[45],"While":[46],"traditional":[47],"methods":[48],"formulate":[49],"problem":[51],"inference":[53],"on":[54,142],"sequence":[56],"segments,":[59],"we":[60,106],"hierarchical":[63],"approach,":[64],"LIGHTEN,":[65],"to":[66,70],"learn":[67],"visual":[68,113,155],"features":[69,156],"effectively":[71],"capture":[72],"spatio-temporal":[73],"cues":[74],"at":[75,164],"multiple":[76],"granularities":[77],"Unlike":[81],"current":[82],"approaches,":[83],"LIGHTEN":[84,161],"avoids":[85],"using":[86,110],"ground":[87],"truth":[88],"data":[89],"like":[90],"depth":[91],"maps":[92],"or":[93],"3D":[94],"human":[95],"pose,":[96],"thus":[97],"increasing":[98],"generalization":[99],"across":[100],"non-RGBD":[101],"datasets":[102],"well.":[104],"Furthermore,":[105],"achieve":[107,124],"same":[109],"only":[111],"features,":[114],"instead":[115],"commonly":[118],"used":[119],"hand-crafted":[120],"spatial":[121],"features.":[122],"We":[123],"state-of-the-art":[125],"results":[126,141],"human-object":[128],"interaction":[129],"detection":[130,146],"(88.9%":[131],"92.6%)":[133],"anticipation":[135],"tasks":[136],"CAD-120":[138],"competitive":[140],"image":[143],"based":[144,157],"HOI":[145],"V-COCO":[148],"dataset,":[149],"setting":[150],"new":[152],"benchmark":[153],"for":[154,160],"approaches.":[158],"Code":[159],"is":[162],"available":[163],"https://github.com/praneeth11009/LIGHTEN-Learning-Interactions-with-Graphs-and-Hierarchical-TEmporal-Networks-for-HOI":[165]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4}],"updated_date":"2026-05-24T08:33:08.758527","created_date":"2020-11-09T00:00:00"}