{"id":"https://openalex.org/W7166653019","doi":"https://doi.org/10.48550/arxiv.2606.30024","title":"IBRSteG: Learning a Generalizable Steganography Framework for 3D Gaussian Splatting","display_name":"IBRSteG: Learning a Generalizable Steganography Framework for 3D Gaussian Splatting","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166653019","doi":"https://doi.org/10.48550/arxiv.2606.30024"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.30024","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30024","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"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.2606.30024","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125072235","display_name":"Fanye Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Fanye","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137630743","display_name":"Hongyu Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Hongyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139687636","display_name":"Yu Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039597152","display_name":"B Dianxuan Gong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Boyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139700203","display_name":"Jie Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5015941605","display_name":"J Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Jiwen","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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9532999992370605,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9532999992370605,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.013299999758601189,"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":0.003700000001117587,"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/steganography","display_name":"Steganography","score":0.901199996471405},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.807699978351593},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6402000188827515},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.5460000038146973},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5357000231742859},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4975000023841858},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.447299987077713},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4275999963283539}],"concepts":[{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.901199996471405},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.807699978351593},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7998999953269958},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6402000188827515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.61080002784729},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.5460000038146973},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5357000231742859},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4975000023841858},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.447299987077713},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4275999963283539},{"id":"https://openalex.org/C3073032","wikidata":"https://www.wikidata.org/wiki/Q15912075","display_name":"Information hiding","level":3,"score":0.42089998722076416},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.41670000553131104},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3953000009059906},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.39160001277923584},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.357699990272522},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3400000035762787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.319599986076355},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3188000023365021},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.28450000286102295},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27480000257492065}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.30024","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30024","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.30024","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30024","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.41931432485580444,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2],"deep":[3],"learning":[4,139],"have":[5],"notably":[6],"improved":[7],"steganographic":[8,15,52,118],"message":[9],"hiding.":[10],"However,":[11],"designing":[12],"a":[13,37,51,72,93,97,111],"generalizable":[14,38],"approach":[16],"for":[17,40],"3D":[18,26,69,74,107,127],"Gaussian":[19,75,108,128],"Splatting":[20],"(3DGS)":[21],"that":[22,43,78,95,160],"can":[23,162],"embed":[24],"meaningful":[25],"scene":[27],"content":[28],"remains":[29],"challenging.":[30],"In":[31],"this":[32],"paper,":[33],"we":[34,67,87],"propose":[35],"IBRSteG,":[36],"framework":[39],"3DGS":[41,82,152],"steganography":[42,70],"enables":[44],"undetectable":[45],"concealment":[46],"of":[47,105],"secret":[48,106],"scenes":[49,119,166],"within":[50],"scene.":[53],"Unlike":[54],"existing":[55],"approaches":[56],"whose":[57],"parameter":[58],"generation":[59],"is":[60,178],"rigidly":[61],"coupled":[62],"with":[63,137,167],"the":[64,103,117],"specific":[65],"scene,":[66,113],"formulate":[68],"as":[71],"feed-forward":[73],"embedding":[76,99],"process":[77],"generalizes":[79],"across":[80],"different":[81,165],"scenes.":[83,153],"To":[84],"realize":[85],"this,":[86],"introduce":[88],"GAS":[89],"(Gaussian":[90],"Attributes":[91],"Steganographer),":[92],"network":[94],"learns":[96],"scene-independent":[98],"function":[100],"by":[101],"injecting":[102],"attributes":[104,134],"points":[109],"into":[110,129],"cover":[112],"thereby":[114,147],"directly":[115],"reconstructing":[116],"without":[120],"per-scene":[121],"finetuning":[122],"or":[123],"optimization.":[124],"By":[125],"transforming":[126],"these":[130,133],"structured":[131,145],"attributes,":[132],"are":[135],"compatible":[136],"2D":[138],"paradigms":[140],"and":[141,171,175],"benefit":[142],"from":[143],"their":[144],"nature,":[146],"enhancing":[148],"generalization":[149],"to":[150],"unseen":[151],"Extensive":[154],"experiments":[155],"on":[156],"established":[157],"datasets":[158],"demonstrate":[159],"IBRSteG":[161],"effectively":[163],"conceal":[164],"high":[168],"visual":[169],"quality,":[170],"achieves":[172],"superior":[173],"capacity":[174],"security.":[176],"Code":[177],"available":[179],"at":[180],"https://github.com/LingXiang2023/IBRSteG.":[181]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-01T00:00:00"}
