{"id":"https://openalex.org/W4415964102","doi":"https://doi.org/10.48550/arxiv.2510.17384","title":"Closed-Loop Transfer for Weakly-supervised Affordance Grounding","display_name":"Closed-Loop Transfer for Weakly-supervised Affordance Grounding","publication_year":2025,"publication_date":"2025-10-20","ids":{"openalex":"https://openalex.org/W4415964102","doi":"https://doi.org/10.48550/arxiv.2510.17384"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2510.17384","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.17384","pdf_url":"https://arxiv.org/pdf/2510.17384","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.17384","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102705973","display_name":"Jiajin Tang","orcid":"https://orcid.org/0009-0002-2906-8941"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tang, Jiajin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101905330","display_name":"Zhiqiang Wei","orcid":"https://orcid.org/0000-0002-2774-3168"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Zhengxuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103095930","display_name":"Zheng Ge","orcid":"https://orcid.org/0000-0001-8770-2555"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Ge","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5012166205","display_name":"Sibei Yang","orcid":"https://orcid.org/0000-0002-8144-7351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Sibei","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102705973"],"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5302000045776367,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5302000045776367,"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":0.08470000326633453,"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":0.08209999650716782,"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/endocentric-and-exocentric","display_name":"Endocentric and exocentric","score":0.9771999716758728},{"id":"https://openalex.org/keywords/affordance","display_name":"Affordance","score":0.9369000196456909},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6464999914169312},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5784000158309937},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.45680001378059387},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4025999903678894},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.35510000586509705},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.34450000524520874}],"concepts":[{"id":"https://openalex.org/C131042201","wikidata":"https://www.wikidata.org/wiki/Q493198","display_name":"Endocentric and exocentric","level":4,"score":0.9771999716758728},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.9369000196456909},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6464999914169312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6123999953269958},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5784000158309937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.564300000667572},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4875999987125397},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.45680001378059387},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36980000138282776},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.35510000586509705},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.3190999925136566},{"id":"https://openalex.org/C3019064422","wikidata":"https://www.wikidata.org/wiki/Q1181947","display_name":"Third person","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C23746413","wikidata":"https://www.wikidata.org/wiki/Q1141379","display_name":"Seam carving","level":3,"score":0.2574999928474426},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2510.17384","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.17384","pdf_url":"https://arxiv.org/pdf/2510.17384","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2510.17384","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.17384","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.17384","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.17384","pdf_url":"https://arxiv.org/pdf/2510.17384","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/W4415964102.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Humans":[0],"can":[1],"perform":[2],"previously":[3],"unexperienced":[4],"interactions":[5],"with":[6,14,38],"novel":[7,72],"objects":[8],"simply":[9],"by":[10,22,149],"observing":[11],"others":[12],"engage":[13],"them.":[15],"Weakly-supervised":[16],"affordance":[17,43],"grounding":[18],"mimics":[19],"this":[20,67],"process":[21],"learning":[23],"to":[24,53,82,88,108],"locate":[25],"object":[26,143],"regions":[27,145],"that":[28,75,125],"enable":[29],"actions":[30],"on":[31,133],"egocentric":[32,54,83,114],"images,":[33],"using":[34],"exocentric":[35,47,81,90,117],"interaction":[36,64,144],"images":[37,48,55,118],"image-level":[39],"annotations.":[40],"However,":[41],"extracting":[42],"knowledge":[44,79,91,106,121],"solely":[45],"from":[46,80],"and":[49,104,115,135],"transferring":[50],"it":[51],"one-way":[52],"limits":[56],"the":[57,150],"applicability":[58],"of":[59],"previous":[60],"works":[61],"in":[62],"complex":[63],"scenarios.":[65],"Instead,":[66],"study":[68],"introduces":[69],"LoopTrans,":[70,94],"a":[71],"closed-loop":[73],"framework":[74],"not":[76],"only":[77],"transfers":[78,86],"but":[84],"also":[85],"back":[87],"enhance":[89],"extraction.":[92],"Within":[93],"several":[95],"innovative":[96],"mechanisms":[97],"are":[98,146],"introduced,":[99],"including":[100],"unified":[101],"cross-modal":[102],"localization":[103],"denoising":[105],"distillation,":[107],"bridge":[109],"domain":[110],"gaps":[111],"between":[112],"object-centered":[113],"interaction-centered":[116],"while":[119],"enhancing":[120],"transfer.":[122],"Experiments":[123],"show":[124],"LoopTrans":[126],"achieves":[127],"consistent":[128],"improvements":[129],"across":[130],"all":[131],"metrics":[132],"image":[134],"video":[136],"benchmarks,":[137],"even":[138],"handling":[139],"challenging":[140],"scenarios":[141],"where":[142],"fully":[147],"occluded":[148],"human":[151],"body.":[152]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-22T00:00:00"}
