{"id":"https://openalex.org/W4403717190","doi":"https://doi.org/10.1145/3698132","title":"Towards Adapting CLIP for Gaze Object Prediction","display_name":"Towards Adapting CLIP for Gaze Object Prediction","publication_year":2024,"publication_date":"2024-10-24","ids":{"openalex":"https://openalex.org/W4403717190","doi":"https://doi.org/10.1145/3698132"},"language":"en","primary_location":{"id":"doi:10.1145/3698132","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3698132","pdf_url":null,"source":{"id":"https://openalex.org/S4210183893","display_name":"Proceedings of the ACM on Human-Computer Interaction","issn_l":"2573-0142","issn":["2573-0142"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Human-Computer Interaction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091224826","display_name":"Dazhi Chen","orcid":"https://orcid.org/0009-0006-0783-6881"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dazhi Chen","raw_affiliation_strings":["Guizhou University, Guiyang, China"],"raw_orcid":"https://orcid.org/0009-0006-0783-6881","affiliations":[{"raw_affiliation_string":"Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085251823","display_name":"Gang Gou","orcid":"https://orcid.org/0009-0005-2055-2157"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Gou","raw_affiliation_strings":["Guizhou University, Guiyang, China"],"raw_orcid":"https://orcid.org/0009-0005-2055-2157","affiliations":[{"raw_affiliation_string":"Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17209588,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"ISS","first_page":"155","last_page":"164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T12740","display_name":"Gait Recognition and Analysis","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9933000206947327,"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/gaze","display_name":"Gaze","score":0.8659161925315857},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5704953670501709},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5192499160766602},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5182409286499023},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4686174988746643},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.426181435585022},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.423747718334198},{"id":"https://openalex.org/keywords/communication","display_name":"Communication","score":0.3642922043800354},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.32006996870040894}],"concepts":[{"id":"https://openalex.org/C2779916870","wikidata":"https://www.wikidata.org/wiki/Q14467155","display_name":"Gaze","level":2,"score":0.8659161925315857},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5704953670501709},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5192499160766602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5182409286499023},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4686174988746643},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.426181435585022},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.423747718334198},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.3642922043800354},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32006996870040894}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3698132","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3698132","pdf_url":null,"source":{"id":"https://openalex.org/S4210183893","display_name":"Proceedings of the ACM on Human-Computer Interaction","issn_l":"2573-0142","issn":["2573-0142"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Human-Computer Interaction","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W614920952","https://openalex.org/W1536680647","https://openalex.org/W1896788142","https://openalex.org/W1981276685","https://openalex.org/W2096037448","https://openalex.org/W2102605133","https://openalex.org/W2806089969","https://openalex.org/W2889006914","https://openalex.org/W2963037989","https://openalex.org/W2976818183","https://openalex.org/W3035735638","https://openalex.org/W3096279628","https://openalex.org/W3185469516","https://openalex.org/W3188642398","https://openalex.org/W4293253477","https://openalex.org/W4313061846","https://openalex.org/W6600757733","https://openalex.org/W6818723395","https://openalex.org/W6853553725"],"related_works":["https://openalex.org/W1880689012","https://openalex.org/W3014378845","https://openalex.org/W4240909707","https://openalex.org/W2059546927","https://openalex.org/W3207760378","https://openalex.org/W4386072035","https://openalex.org/W2562758970","https://openalex.org/W1986970529","https://openalex.org/W1563178652","https://openalex.org/W4399144619"],"abstract_inverted_index":{"This":[0],"paper":[1],"aims":[2],"to":[3,40,50,96],"investigate":[4],"the":[5,52,69,74,78,83,89,102],"problem":[6],"of":[7,55,92],"gaze":[8,23,59],"object":[9,24],"prediction":[10,70],"in":[11],"single":[12],"images.":[13],"We":[14,99],"propose":[15],"an":[16],"application-friendly":[17],"network":[18],"based":[19],"on":[20],"CLIP":[21],"for":[22],"prediction.":[25],"To":[26],"avoid":[27],"domain":[28],"bias,":[29],"we":[30,44,63],"utilize":[31],"a":[32,46,65],"shallow":[33],"feature":[34],"adapter":[35],"that":[36,67],"transfers":[37],"pre-trained":[38],"features":[39],"target-oriented":[41],"ones.":[42],"Secondly,":[43],"introduce":[45,64],"pooling":[47],"attention":[48],"block":[49],"exploit":[51],"joint":[53],"representation":[54],"multimodal":[56],"elements,":[57],"reducing":[58],"point":[60],"deviation.":[61],"Additionally,":[62],"loss":[66],"measures":[68],"quality":[71],"by":[72],"comparing":[73],"distribution":[75],"difference":[76],"between":[77],"model's":[79],"predictions":[80],"heatmaps":[81],"and":[82],"ground":[84],"truth.":[85],"Extensive":[86],"experiments":[87],"demonstrate":[88],"superior":[90],"performance":[91],"our":[93],"model":[94],"compared":[95],"previous":[97],"models.":[98],"will":[100],"provide":[101],"method":[103],"code":[104],"at:":[105],"https://github.com/fadaishaitaiyang/CCLIP.git.":[106]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}