{"id":"https://openalex.org/W7140227884","doi":"https://doi.org/10.48550/arxiv.2603.20310","title":"GraphiContact: Pose-aware Human-Scene Robust Contact Perception for Interactive Systems","display_name":"GraphiContact: Pose-aware Human-Scene Robust Contact Perception for Interactive Systems","publication_year":2026,"publication_date":"2026-03-19","ids":{"openalex":"https://openalex.org/W7140227884","doi":"https://doi.org/10.48550/arxiv.2603.20310"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.20310","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20310","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.2603.20310","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Lin, Xiaojian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Xiaojian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Shen, Yaomin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Yaomin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ma, Junyuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Junyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Sun, Yujie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Yujie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Bu, Chengqing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bu, Chengqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zhang, Wenxin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wenxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Zhang, Zongzheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zongzheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Fei, Hao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fei, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jin, Lei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Zhao, Hao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Hao","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/T10812","display_name":"Human Pose and Action Recognition","score":0.870199978351593,"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":0.870199978351593,"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/T12290","display_name":"Human Motion and Animation","score":0.030300000682473183,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.02459999918937683,"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/robustness","display_name":"Robustness (evolution)","score":0.6446999907493591},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5830000042915344},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5472000241279602},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5001000165939331},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.37130001187324524},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.36880001425743103},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.34860000014305115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6972000002861023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6643000245094299},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6446999907493591},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5830000042915344},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5472000241279602},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5001000165939331},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43560001254081726},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41760000586509705},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.37130001187324524},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.36880001425743103},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3345000147819519},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3075999915599823},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2799000144004822},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.25279998779296875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.20310","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20310","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.2603.20310","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.20310","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Monocular":[0],"vertex-level":[1,67],"human-scene":[2,98],"contact":[3,43,50,68,99,153],"prediction":[4,51,154],"is":[5],"a":[6,40,82,113],"fundamental":[7],"capability":[8],"for":[9,42],"interactive":[10],"systems":[11],"such":[12],"as":[13,39],"assistive":[14],"monitoring,":[15],"embodied":[16],"AI,":[17],"and":[18,72,95,127,155,171,174],"rehabilitation":[19],"analysis.":[20],"In":[21],"this":[22,26,77],"work,":[23],"we":[24,79,110],"study":[25],"task":[27],"jointly":[28],"with":[29,120],"single-image":[30],"3D":[31,56,156,168],"human":[32,57,88,157,169],"mesh":[33],"reconstruction,":[34],"using":[35],"reconstructed":[36,102],"body":[37],"geometry":[38],"scaffold":[41],"reasoning.":[44],"Existing":[45],"approaches":[46],"either":[47],"focus":[48],"on":[49,100,141,151,162],"without":[52,63],"sufficiently":[53],"exploiting":[54],"explicit":[55],"priors,":[58],"or":[59],"emphasize":[60],"pose/mesh":[61],"reconstruction":[62,170],"directly":[64],"optimizing":[65],"robust":[66],"inference":[69,136],"under":[70],"occlusion":[71,126],"perceptual":[73],"noise.":[74],"To":[75,104],"address":[76],"gap,":[78],"propose":[80],"GraphiContact,":[81],"pose-aware":[83],"framework":[84],"that":[85,146],"transfers":[86],"complementary":[87],"priors":[89],"from":[90],"two":[91],"pretrained":[92],"Transformer":[93],"encoders":[94],"predicts":[96],"per-vertex":[97],"the":[101,163],"mesh.":[103],"improve":[105],"robustness":[106],"in":[107],"real-world":[108],"scenarios,":[109],"further":[111],"introduce":[112],"Single-Image":[114],"Multi-Infer":[115],"Uncertainty":[116],"(SIMU)":[117],"training":[118,131],"strategy":[119],"token-level":[121],"adaptive":[122],"routing,":[123],"which":[124],"simulates":[125],"noisy":[128],"observations":[129],"during":[130],"while":[132],"preserving":[133],"efficient":[134],"single-branch":[135],"at":[137,179],"test":[138],"time.":[139],"Experiments":[140],"five":[142],"benchmark":[143],"datasets":[144],"show":[145],"GraphiContact":[147,164],"achieves":[148],"consistent":[149],"gains":[150],"both":[152],"reconstruction.":[158],"Our":[159],"code,":[160],"based":[161],"method,":[165],"provides":[166],"comprehensive":[167],"interaction":[172],"analysis,":[173],"will":[175],"be":[176],"publicly":[177],"available":[178],"https://github.com/Aveiro-Lin/GraphiContact.":[180]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-25T00:00:00"}
