{"id":"https://openalex.org/W4410790424","doi":"https://doi.org/10.1145/3729416","title":"S3PL : Self-Supervised Segmentation for Robust Pupil Localization","display_name":"S3PL : Self-Supervised Segmentation for Robust Pupil Localization","publication_year":2025,"publication_date":"2025-05-26","ids":{"openalex":"https://openalex.org/W4410790424","doi":"https://doi.org/10.1145/3729416"},"language":"en","primary_location":{"id":"doi:10.1145/3729416","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3729416","pdf_url":null,"source":{"id":"https://openalex.org/S4210220973","display_name":"Proceedings of the ACM on Computer Graphics and Interactive Techniques","issn_l":"2577-6193","issn":["2577-6193"],"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 Computer Graphics and Interactive Techniques","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/A5061587452","display_name":"P. Vishnuvardhan","orcid":"https://orcid.org/0009-0005-4736-1617"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Purma VishnuVardhan","raw_affiliation_strings":["Mercedes Benz Research and Development India, Bangalore, India"],"raw_orcid":"https://orcid.org/0009-0005-4736-1617","affiliations":[{"raw_affiliation_string":"Mercedes Benz Research and Development India, Bangalore, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117718047","display_name":"Vignan Gummadi","orcid":"https://orcid.org/0009-0003-8353-6387"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vignan Gummadi","raw_affiliation_strings":["Mercedes Benz Research and Development India, Bangalore, India"],"raw_orcid":"https://orcid.org/0009-0003-8353-6387","affiliations":[{"raw_affiliation_string":"Mercedes Benz Research and Development India, Bangalore, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117718048","display_name":"Ashwini Kundranda Poovaiah","orcid":"https://orcid.org/0009-0003-6314-8555"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ashwini Kundranda Poovaiah","raw_affiliation_strings":["Mercedes Benz Research and Development India, Bengaluru, Karanataka, India"],"raw_orcid":"https://orcid.org/0009-0003-6314-8555","affiliations":[{"raw_affiliation_string":"Mercedes Benz Research and Development India, Bengaluru, Karanataka, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039917779","display_name":"L. R. D. Murthy","orcid":"https://orcid.org/0000-0002-7039-6763"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lrd Murthy","raw_affiliation_strings":["Mercedes Benz Research and Development India, Bangalore, India"],"raw_orcid":"https://orcid.org/0000-0002-7039-6763","affiliations":[{"raw_affiliation_string":"Mercedes Benz Research and Development India, Bangalore, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.08771136,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"2","first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9987000226974487,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9987000226974487,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9934999942779541,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9908000230789185,"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/segmentation","display_name":"Segmentation","score":0.6248865723609924},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.607215166091919},{"id":"https://openalex.org/keywords/pupil","display_name":"Pupil","score":0.558698296546936},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5295321345329285},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46648338437080383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3598824739456177},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.24893692135810852},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.07169625163078308}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6248865723609924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.607215166091919},{"id":"https://openalex.org/C2777394604","wikidata":"https://www.wikidata.org/wiki/Q173318","display_name":"Pupil","level":2,"score":0.558698296546936},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5295321345329285},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46648338437080383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3598824739456177},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.24893692135810852},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.07169625163078308}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3729416","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3729416","pdf_url":null,"source":{"id":"https://openalex.org/S4210220973","display_name":"Proceedings of the ACM on Computer Graphics and Interactive Techniques","issn_l":"2577-6193","issn":["2577-6193"],"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 Computer Graphics and Interactive Techniques","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1536729381","https://openalex.org/W1945120929","https://openalex.org/W2008997129","https://openalex.org/W2017617273","https://openalex.org/W2090234410","https://openalex.org/W2162136544","https://openalex.org/W2177921452","https://openalex.org/W2256808982","https://openalex.org/W2272545788","https://openalex.org/W2295566235","https://openalex.org/W2516431700","https://openalex.org/W2593414223","https://openalex.org/W2734349601","https://openalex.org/W2779695644","https://openalex.org/W2805466601","https://openalex.org/W2805931081","https://openalex.org/W2883558655","https://openalex.org/W2889334143","https://openalex.org/W2891963238","https://openalex.org/W2941240724","https://openalex.org/W2944289193","https://openalex.org/W2947551409","https://openalex.org/W2949442988","https://openalex.org/W2962793481","https://openalex.org/W2963351448","https://openalex.org/W2964098128","https://openalex.org/W2969498159","https://openalex.org/W2970574533","https://openalex.org/W2980761379","https://openalex.org/W2997768619","https://openalex.org/W3038091703","https://openalex.org/W3038932711","https://openalex.org/W3080646814","https://openalex.org/W3112139896","https://openalex.org/W3113141251","https://openalex.org/W3138081252","https://openalex.org/W3164563012","https://openalex.org/W3207929382","https://openalex.org/W3210728012","https://openalex.org/W4289743905","https://openalex.org/W4292446854","https://openalex.org/W4293154803","https://openalex.org/W4320013936","https://openalex.org/W4389649841","https://openalex.org/W4399203220","https://openalex.org/W4402125028"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"The":[0,151],"task":[1,85],"of":[2,147,157,175],"pupil":[3,77,102,132,176],"localization":[4,103,133],"is":[5],"an":[6,81,155],"imperative":[7],"step":[8],"for":[9,59,140],"any":[10],"gaze":[11],"estimation":[12,79],"and":[13,28,35,61,86,100,126,128,136,168],"eye":[14],"tracking":[15],"systems.":[16],"Due":[17],"to":[18,52,64,92,97,143],"the":[19,93,121,130,145,148,180],"challenges":[20],"induced":[21],"by":[22],"diverse":[23],"factors":[24],"like":[25],"illumination,":[26],"reflections":[27],"noise,":[29],"researchers":[30],"have":[31,47],"proposed":[32,149,152],"several":[33],"classical":[34,53],"learning":[36,44,106],"based":[37,45],"approaches":[38],"addressing":[39],"this":[40,73],"problem.":[41],"Even":[42],"though":[43],"methods":[46],"shown":[48],"superior":[49],"accuracy":[50],"compared":[51],"methods,":[54],"they":[55],"require":[56],"extensive":[57],"annotations":[58],"training":[60],"are":[62,138],"prone":[63],"poor":[65],"cross-dataset":[66],"performance":[67],"on":[68,113,160,163,166,170],"new":[69],"unseen":[70],"scenarios.":[71],"In":[72],"work,":[74],"we":[75,109],"formulated":[76],"center":[78],"as":[80],"unpaired":[82],"image-to-image":[83],"translation":[84],"introduced":[87],"a":[88],"novel":[89],"loss":[90],"function":[91],"existing":[94],"CycleGAN":[95],"framework":[96],"achieve":[98],"robust":[99],"accurate":[101],"using":[104],"self-supervised":[105],"paradigm.":[107],"Further,":[108],"evaluated":[110],"our":[111],"method":[112,153],"four":[114],"publicly":[115],"available":[116],"datasets,":[117],"Labelled":[118],"pupils":[119],"in":[120,173],"wild":[122],"(LPW),":[123],"OpenEDS,":[124,164],"\u015awirski,":[125,135,167],"NVGaze,":[127],"reported":[129],"state-of-the-art":[131],"performance.":[134],"NVGaze":[137,171],"used":[139],"cross-data":[141],"evaluation":[142],"understand":[144],"generalizability":[146],"method.":[150],"achieved":[154],"improvement":[156],"around":[158],"16%":[159],"LPW,":[161],"21%":[162],"5%":[165],"14%":[169],"datasets":[172],"terms":[174],"detection":[177],"rate":[178],"over":[179],"conventional":[181],"methods.":[182]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
