{"id":"https://openalex.org/W6907457048","doi":"https://doi.org/10.2312/stag.20241352","title":"Semantic Stylization and Shading via Segmentation Atlas utilizing Deep Learning Approaches","display_name":"Semantic Stylization and Shading via Segmentation Atlas utilizing Deep Learning Approaches","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W6907457048","doi":"https://doi.org/10.2312/stag.20241352"},"language":"en","primary_location":{"id":"pmh:oai:publica.fraunhofer.de:publica/479148","is_oa":true,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/479148","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"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":"conference paper"},"type":"conference-paper","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://publica.fraunhofer.de/handle/publica/479148","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sinha, Saptarshi Neil","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sinha, Saptarshi Neil","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"K\u00fchn, Paul Julius","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"K\u00fchn, Paul Julius","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Rojtberg, Pavel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rojtberg, Pavel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Graf, Holger","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Graf, Holger","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Kuijper, Arjan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuijper, Arjan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Weinmann, Michael","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weinmann, Michael","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":0.6963,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.81623347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.5171999931335449,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.5171999931335449,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.19110000133514404,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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":0.0658000037074089,"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":0.7401999831199646},{"id":"https://openalex.org/keywords/atlas","display_name":"Atlas (anatomy)","score":0.5565999746322632},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5444999933242798},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47929999232292175},{"id":"https://openalex.org/keywords/ghosting","display_name":"Ghosting","score":0.4189000129699707},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4034999907016754},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.35850000381469727},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3434000015258789}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7591999769210815},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7401999831199646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7350000143051147},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5712000131607056},{"id":"https://openalex.org/C2776673561","wikidata":"https://www.wikidata.org/wiki/Q655357","display_name":"Atlas (anatomy)","level":2,"score":0.5565999746322632},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5444999933242798},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47929999232292175},{"id":"https://openalex.org/C2780531524","wikidata":"https://www.wikidata.org/wiki/Q551540","display_name":"Ghosting","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4034999907016754},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.35850000381469727},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3434000015258789},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C3019007443","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3d model","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2946999967098236},{"id":"https://openalex.org/C3018391215","wikidata":"https://www.wikidata.org/wiki/Q2449377","display_name":"Flat surface","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2833999991416931},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2623000144958496}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:publica.fraunhofer.de:publica/479148","is_oa":true,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/479148","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"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":"conference paper"},{"id":"doi:10.2312/stag.20241352","is_oa":true,"landing_page_url":"https://doi.org/10.2312/stag.20241352","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":null,"is_oa":false,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:publica.fraunhofer.de:publica/479148","is_oa":true,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/479148","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"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":"conference paper"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7812324166297913,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,20,78,89,108,132],"novel":[3],"hybrid":[4,21],"approach":[5,22,145],"for":[6,149],"semantic":[7,128],"stylization":[8,65,96,118],"of":[9,12,57,77,99,102,119],"surface":[10,33,85,120],"materials":[11,121],"3D":[13,42,64,104,140],"models":[14],"while":[15],"preserving":[16],"shading.":[17],"Based":[18],"on":[19,25,30,88],"that":[23,113],"builds":[24],"directly":[26],"applying":[27],"style":[28,111],"transfer":[29,112],"the":[31,58,74,83,95,103,115],"object":[32,84],"obtained":[34],"by":[35,62],"learning-based":[36],"or":[37,44,54,117],"traditional":[38],"methods":[39,71],"such":[40],"as":[41],"scanners":[43],"structured":[45],"light":[46],"systems,":[47],"thereby":[48],"overcoming":[49],"artifacts":[50],"like":[51],"halos,":[52],"ghosting":[53],"lacking":[55],"quality":[56],"geometric":[59],"representation":[60],"produced":[61],"other":[63],"methods.":[66],"For":[67],"this":[68],"purpose,":[69],"our":[70,144],"involves":[72],"(i)":[73],"initial":[75],"generation":[76],"segmentation":[79,141],"map":[80],"parameterized":[81],"over":[82],"inferred":[86],"based":[87],"deep-learning-based":[90],"foundation":[91],"model":[92],"to":[93],"guide":[94],"and":[97,106,142,157],"shading":[98],"different":[100],"regions":[101],"model,":[105],"(ii)":[107],"subsequent":[109],"2D":[110],"allows":[114],"exchange":[116],"in":[122,131],"high":[123],"quality.":[124],"By":[125],"delivering":[126],"high-quality":[127],"perceptive":[129],"reconstructions":[130],"shorter":[133],"timeframe":[134],"than":[135],"current":[136],"approaches":[137],"using":[138],"manual":[139],"stylization,":[143],"holds":[146],"significant":[147],"potential":[148],"various":[150],"application":[151],"scenarios":[152],"including":[153],"creative":[154],"design,":[155],"architecture":[156],"cultural":[158],"heritage.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
