{"id":"https://openalex.org/W7155190006","doi":"https://doi.org/10.48550/arxiv.2604.19480","title":"Deep Sprite-based Image Models: An Analysis","display_name":"Deep Sprite-based Image Models: An Analysis","publication_year":2026,"publication_date":"2026-04-21","ids":{"openalex":"https://openalex.org/W7155190006","doi":"https://doi.org/10.48550/arxiv.2604.19480"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.19480","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19480","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":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.2604.19480","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134232779","display_name":"Zeynep Sonat Baltac\u0131","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baltac\u0131, Zeynep Sonat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134306187","display_name":"Romain Loiseau","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Loiseau, Romain","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5061634216","display_name":"Mathieu Aubry","orcid":"https://orcid.org/0000-0002-3804-0193"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aubry, Mathieu","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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.3368000090122223,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.3368000090122223,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.29429998993873596,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.04129999876022339,"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/cluster-analysis","display_name":"Cluster analysis","score":0.6215000152587891},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.586899995803833},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.569100022315979},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5062000155448914},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.49230000376701355},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4885999858379364},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4830999970436096},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.46799999475479126}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.711899995803833},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6215000152587891},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6164000034332275},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.586899995803833},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.569100022315979},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5062000155448914},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5024999976158142},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.49230000376701355},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4885999858379364},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4830999970436096},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.46799999475479126},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4052000045776367},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3910999894142151},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3874000012874603},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.3522999882698059},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.32100000977516174},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.3133000135421753},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.19480","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19480","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.19480","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19480","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":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":{"While":[0],"foundation":[1],"models":[2,63,145],"drive":[3],"steady":[4],"progress":[5],"in":[6,25,65,147],"image":[7,41,52,113,124],"segmentation":[8,125],"and":[9,51,54,75,96,143],"diffusion":[10],"algorithms":[11],"compose":[12],"always":[13],"more":[14],"realistic":[15],"images,":[16],"the":[17,87,128,135],"seemingly":[18],"simple":[19],"problem":[20],"of":[21,28,58,89,137],"identifying":[22],"recurrent":[23],"patterns":[24],"a":[26,110],"collection":[27],"images":[29,80,146],"remains":[30],"very":[31],"much":[32],"open.":[33],"In":[34],"this":[35,106],"paper,":[36],"we":[37],"focus":[38],"on":[39,101,118,127],"sprite-based":[40,112],"decomposition":[42,53,114],"models,":[43],"which":[44],"have":[45],"shown":[46],"some":[47],"promise":[48],"for":[49],"clustering":[50,102],"are":[55],"appealing":[56],"because":[57],"their":[59,90,93],"high":[60],"interpretability.":[61],"These":[62],"come":[64],"different":[66],"flavors,":[67],"need":[68],"to":[69,72,77,79,108],"be":[70],"tailored":[71],"specific":[73],"datasets,":[74],"struggle":[76],"scale":[78],"with":[81,120,134],"many":[82],"objects.":[83],"We":[84,104],"dive":[85],"into":[86],"details":[88],"design,":[91],"identify":[92],"core":[94],"components,":[95],"perform":[97],"an":[98,148],"extensive":[99],"analysis":[100,107],"benchmarks.":[103],"leverage":[105],"propose":[109],"deep":[111],"method":[115],"that":[116],"performs":[117],"par":[119],"state-of-the-art":[121],"unsupervised":[122],"class-aware":[123],"methods":[126],"standard":[129],"CLEVR":[130],"benchmark,":[131],"scales":[132],"linearly":[133],"number":[136],"objects,":[138],"identifies":[139],"explicitly":[140],"object":[141],"categories,":[142],"fully":[144],"easily":[149],"interpretable":[150],"way.":[151]},"counts_by_year":[],"updated_date":"2026-07-11T05:44:25.926202","created_date":"2026-04-23T00:00:00"}
