{"id":"https://openalex.org/W4415962877","doi":"https://doi.org/10.1109/iccv51701.2025.01217","title":"Capturing Head Avatar with Hand Contacts from a Monocular Video","display_name":"Capturing Head Avatar with Hand Contacts from a Monocular Video","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4415962877","doi":"https://doi.org/10.1109/iccv51701.2025.01217"},"language":null,"primary_location":{"id":"doi:10.1109/iccv51701.2025.01217","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01217","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.17181","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027141821","display_name":"Haonan He","orcid":"https://orcid.org/0009-0001-9720-6691"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"He, Haonan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101751449","display_name":"Yufeng Zheng","orcid":"https://orcid.org/0009-0004-4125-9446"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Yufeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100612521","display_name":"Jie Song","orcid":"https://orcid.org/0000-0003-4111-2570"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027141821"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30631152,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"13099","last_page":"13108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.7250000238418579,"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/T11448","display_name":"Face recognition and analysis","score":0.7250000238418579,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.04470000043511391,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.03319999948143959,"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/monocular","display_name":"Monocular","score":0.6776000261306763},{"id":"https://openalex.org/keywords/avatar","display_name":"Avatar","score":0.6187999844551086},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5709999799728394},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4668999910354614},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.415800005197525},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.38760000467300415},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.38100001215934753},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.36980000138282776},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.35920000076293945}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7652000188827515},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7578999996185303},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7454000115394592},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.6776000261306763},{"id":"https://openalex.org/C2777365542","wikidata":"https://www.wikidata.org/wiki/Q83090","display_name":"Avatar","level":2,"score":0.6187999844551086},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5709999799728394},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4668999910354614},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.415800005197525},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.38760000467300415},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.36980000138282776},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3402999937534332},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C98907195","wikidata":"https://www.wikidata.org/wiki/Q5428562","display_name":"Facial motion capture","level":5,"score":0.289000004529953},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.2867000102996826},{"id":"https://openalex.org/C2779881321","wikidata":"https://www.wikidata.org/wiki/Q82714","display_name":"Chin","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C23746413","wikidata":"https://www.wikidata.org/wiki/Q1141379","display_name":"Seam carving","level":3,"score":0.2578999996185303},{"id":"https://openalex.org/C5917680","wikidata":"https://www.wikidata.org/wiki/Q2621825","display_name":"Basis function","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01217","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01217","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2510.17181","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.17181","pdf_url":"https://arxiv.org/pdf/2510.17181","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},{"id":"doi:10.48550/arxiv.2510.17181","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.17181","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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.17181","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.17181","pdf_url":"https://arxiv.org/pdf/2510.17181","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415962877.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Photorealistic":[0],"3D":[1],"head":[2,55],"avatars":[3,56,215],"are":[4,66],"vital":[5],"for":[6,117],"telepresence,":[7],"gaming,":[8],"and":[9,57,77,109,183,231],"VR.":[10],"However,":[11],"most":[12],"methods":[13],"focus":[14],"solely":[15],"on":[16,28,195],"facial":[17,139],"regions,":[18],"ignoring":[19],"natural":[20],"hand-face":[21,63],"interactions,":[22],"such":[23],"as":[24],"a":[25,48,133,142,152,160,172,211],"hand":[26,76,220],"resting":[27],"the":[29,35,58,107,148,185,189,206,237],"chin":[30],"or":[31],"fingers":[32],"gently":[33],"touching":[34],"cheek,":[36],"which":[37],"convey":[38],"cognitive":[39],"states":[40],"like":[41],"pondering.":[42],"In":[43],"this":[44,71],"work,":[45],"we":[46,89,131,170,209],"present":[47],"novel":[49],"framework":[50],"that":[51,175,224],"jointly":[52],"learns":[53],"detailed":[54],"non-rigid":[59],"deformations":[60,140],"induced":[61],"by":[62,167,199],"interactions.":[64,221],"There":[65],"two":[67],"principal":[68],"challenges":[69],"in":[70],"task.":[72],"First,":[73],"naively":[74],"tracking":[75],"face":[78,108,238],"separately":[79],"fails":[80],"to":[81,91,123,137,150,203],"capture":[82,228],"their":[83],"relative":[84],"poses.":[85],"To":[86,128],"overcome":[87],"this,":[88,130],"propose":[90],"combine":[92],"depth":[93],"order":[94],"loss":[95,174],"with":[96,216],"contact":[97,173],"regularization":[98],"during":[99],"pose":[100],"tracking,":[101],"ensuring":[102],"correct":[103],"spatial":[104,162],"relationships":[105],"between":[106],"hand.":[110],"Second,":[111],"no":[112],"publicly":[113],"available":[114],"priors":[115],"exist":[116],"hand-induced":[118,138],"deformations,":[119],"making":[120],"them":[121],"non-trivial":[122],"learn":[124,132],"from":[125,141],"monocular":[126],"videos.":[127],"address":[129],"PCA":[134,156],"basis":[135],"specific":[136],"face-hand":[143],"interaction":[144],"dataset.":[145],"This":[146],"reduces":[147],"problem":[149],"estimating":[151],"compact":[153],"set":[154],"of":[155,188,214,219,236],"parameters":[157],"rather":[158],"than":[159,239],"full":[161],"deformation":[163],"field.":[164],"Furthermore,":[165],"inspired":[166],"physics-based":[168],"simulation,":[169],"incorporate":[171],"provides":[176],"additional":[177],"supervision,":[178],"significantly":[179],"reducing":[180],"interpenetration":[181],"artifacts":[182],"enhancing":[184],"physical":[186],"plausibility":[187],"results.":[190],"We":[191,222],"evaluate":[192,205],"our":[193,225],"approach":[194],"RGB(D)":[196],"videos":[197],"captured":[198],"an":[200],"iPhone.":[201],"Additionally,":[202],"better":[204,229],"reconstructed":[207],"geometry,":[208],"construct":[210],"synthetic":[212],"dataset":[213],"various":[217],"types":[218],"show":[223],"method":[226],"can":[227],"appearance":[230],"more":[232],"accurate":[233],"deforming":[234],"geometry":[235],"SOTA":[240],"surface":[241],"reconstruction":[242],"methods.":[243]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-22T00:00:00"}
