{"id":"https://openalex.org/W7151529080","doi":"https://doi.org/10.48550/arxiv.2604.04016","title":"HOIGS: Human-Object Interaction Gaussian Splatting","display_name":"HOIGS: Human-Object Interaction Gaussian Splatting","publication_year":2026,"publication_date":"2026-04-05","ids":{"openalex":"https://openalex.org/W7151529080","doi":"https://doi.org/10.48550/arxiv.2604.04016"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.04016","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04016","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.04016","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133097617","display_name":"Taewoo Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Taewoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114137441","display_name":"Suwoong Yeom","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yeom, Suwoong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007230069","display_name":"Jisurk Pyun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pyun, Jaehyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051789113","display_name":"Geonho Cha","orcid":"https://orcid.org/0000-0002-3008-4642"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cha, Geonho","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028451951","display_name":"Dongyoon Wee","orcid":"https://orcid.org/0000-0003-0359-146X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wee, Dongyoon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046132980","display_name":"Joonsik Nam","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nam, Joonsik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133081107","display_name":"Yun-Seong Jeong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeong, Yun-Seong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000238164","display_name":"Kyeongbo Kong","orcid":"https://orcid.org/0000-0002-1135-7502"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Kyeongbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133127931","display_name":"Suk-Ju Kang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kang, Suk-Ju","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.5194000005722046,"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":0.5194000005722046,"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":0.3531999886035919,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.022600000724196434,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.637499988079071},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5318999886512756},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4982999861240387},{"id":"https://openalex.org/keywords/deformation","display_name":"Deformation (meteorology)","score":0.399399995803833},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.38659998774528503},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.3846000134944916},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.32829999923706055},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.3001999855041504}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7631999850273132},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.637499988079071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5575000047683716},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5318999886512756},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4982999861240387},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.498199999332428},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4099000096321106},{"id":"https://openalex.org/C204366326","wikidata":"https://www.wikidata.org/wiki/Q3027650","display_name":"Deformation (meteorology)","level":2,"score":0.399399995803833},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.38659998774528503},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.29030001163482666},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.28769999742507935},{"id":"https://openalex.org/C10390562","wikidata":"https://www.wikidata.org/wiki/Q581809","display_name":"Spline (mechanical)","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C68806387","wikidata":"https://www.wikidata.org/wiki/Q2724617","display_name":"Gaussian surface","level":3,"score":0.27090001106262207},{"id":"https://openalex.org/C2779038628","wikidata":"https://www.wikidata.org/wiki/Q7248497","display_name":"Programming by demonstration","level":3,"score":0.26829999685287476},{"id":"https://openalex.org/C181095308","wikidata":"https://www.wikidata.org/wiki/Q1541599","display_name":"Geometric primitive","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.2556999921798706},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.04016","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04016","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.04016","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.04016","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.49685314297676086,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reconstructing":[0],"dynamic":[1,28],"scenes":[2],"with":[3],"complex":[4],"human-object":[5,133],"interactions":[6,134],"is":[7],"a":[8,35,66],"fundamental":[9],"challenge":[10],"in":[11,102],"computer":[12],"vision":[13],"and":[14,63,81,98,107,123],"graphics.":[15],"Existing":[16],"Gaussian":[17,53,125],"Splatting":[18,54],"methods":[19],"either":[20],"rely":[21],"on":[22,112],"human":[23],"pose":[24],"priors":[25],"while":[26],"neglecting":[27],"objects,":[29],"or":[30],"approximate":[31],"all":[32],"motions":[33,97],"within":[34],"single":[36],"field,":[37],"limiting":[38],"their":[39],"ability":[40],"to":[41,75],"capture":[42],"interaction-rich":[43],"dynamics.":[44],"To":[45],"address":[46],"this":[47],"gap,":[48],"we":[49],"propose":[50],"Human-Object":[51],"Interaction":[52],"(HOIGS),":[55],"which":[56],"explicitly":[57,131],"models":[58],"interaction-induced":[59],"deformation":[60,71,100],"between":[61],"humans":[62,80],"objects":[64],"through":[65],"cross-attention-based":[67],"HOI":[68],"module.":[69],"Distinct":[70],"baselines":[72],"are":[73],"employed":[74],"extract":[76],"features:":[77],"HexPlane":[78],"for":[79,86,135],"Cubic":[82],"Hermite":[83],"Spline":[84],"(CHS)":[85],"objects.":[87],"By":[88],"integrating":[89],"these":[90],"heterogeneous":[91],"features,":[92],"HOIGS":[93],"effectively":[94],"captures":[95],"interdependent":[96],"improves":[99],"estimation":[101],"scenarios":[103],"involving":[104],"occlusion,":[105],"contact,":[106],"object":[108],"manipulation.":[109],"Comprehensive":[110],"experiments":[111],"multiple":[113],"datasets":[114],"demonstrate":[115],"that":[116],"our":[117],"method":[118],"consistently":[119],"outperforms":[120],"state-of-the-art":[121],"human-centric":[122],"4D":[124],"approaches,":[126],"highlighting":[127],"the":[128],"importance":[129],"of":[130],"modeling":[132],"high-fidelity":[136],"reconstruction.":[137]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-08T00:00:00"}
