{"id":"https://openalex.org/W7154566380","doi":"https://doi.org/10.48550/arxiv.2604.13153","title":"PatchPoison: Poisoning Multi-View Datasets to Degrade 3D Reconstruction","display_name":"PatchPoison: Poisoning Multi-View Datasets to Degrade 3D Reconstruction","publication_year":2026,"publication_date":"2026-04-14","ids":{"openalex":"https://openalex.org/W7154566380","doi":"https://doi.org/10.48550/arxiv.2604.13153"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.13153","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13153","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":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.2604.13153","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133802234","display_name":"Prajas Wadekar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wadekar, Prajas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099082799","display_name":"Venkata Sai Pranav Bachina","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bachina, Venkata Sai Pranav","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120840755","display_name":"Kunal Bhosikar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhosikar, Kunal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064911856","display_name":"Ankit Gangwal","orcid":"https://orcid.org/0000-0002-8065-3700"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gangwal, Ankit","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133827209","display_name":"Charu Sharma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sharma, Charu","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/T12357","display_name":"Digital Media Forensic Detection","score":0.3361999988555908,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.3361999988555908,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.3285999894142151,"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":0.08630000054836273,"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/pipeline","display_name":"Pipeline (software)","score":0.6984999775886536},{"id":"https://openalex.org/keywords/3d-reconstruction","display_name":"3D reconstruction","score":0.6211000084877014},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.548799991607666},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5339000225067139},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.45730000734329224},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.40709999203681946},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.3544999957084656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.781000018119812},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7332000136375427},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6984999775886536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6884999871253967},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.6211000084877014},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.548799991607666},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5339000225067139},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.4388999938964844},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.40709999203681946},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C2776863239","wikidata":"https://www.wikidata.org/wiki/Q7936601","display_name":"Visual hull","level":3,"score":0.31869998574256897},{"id":"https://openalex.org/C84418412","wikidata":"https://www.wikidata.org/wiki/Q3246940","display_name":"Digital forensics","level":2,"score":0.3125},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C2775853353","wikidata":"https://www.wikidata.org/wiki/Q5416724","display_name":"Event reconstruction","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2712000012397766},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.2630999982357025}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.13153","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13153","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":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.2604.13153","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13153","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.5367642045021057,"display_name":"Peace, Justice and strong institutions","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":{"3D":[0,9,34,54],"Gaussian":[1],"Splatting":[2],"(3DGS)":[3],"has":[4],"recently":[5],"enabled":[6],"highly":[7],"photorealistic":[8],"reconstruction":[10,127],"from":[11,110],"casually":[12],"captured":[13],"multi-view":[14,77,159],"images.":[15],"However,":[16],"this":[17],"accessibility":[18],"raises":[19],"a":[20,47,61,66,76,120,148],"privacy":[21],"concern:":[22],"publicly":[23],"available":[24],"images":[25,136],"or":[26,38],"videos":[27],"can":[28],"be":[29],"exploited":[30],"to":[31,83,139,156],"reconstruct":[32],"detailed":[33],"models":[35],"of":[36,72,88],"scenes":[37],"objects":[39],"without":[40],"the":[41,70,85,111,116,134],"owner's":[42],"consent.":[43],"We":[44],"present":[45],"PatchPoison,":[46],"lightweight":[48],"dataset-poisoning":[49],"method":[50],"that":[51,99],"prevents":[52],"unauthorized":[53],"reconstruction.":[55],"Unlike":[56],"global":[57],"perturbations,":[58],"PatchPoison":[59,142],"injects":[60],"small":[62],"high-frequency":[63],"adversarial":[64],"patch,":[65],"structured":[67],"checkerboard,":[68],"into":[69],"periphery":[71],"each":[73],"image":[74],"in":[75,131],"dataset.":[78],"The":[79],"patch":[80,125],"is":[81],"designed":[82],"corrupt":[84],"feature-matching":[86],"stage":[87],"Structure-from-Motion":[89],"(SfM)":[90],"pipelines":[91],"such":[92],"as":[93],"COLMAP":[94],"by":[95,129],"introducing":[96],"spurious":[97],"correspondences":[98],"systematically":[100],"misalign":[101],"estimated":[102],"camera":[103],"poses.":[104],"Consequently,":[105],"downstream":[106],"3DGS":[107],"optimization":[108],"diverges":[109],"correct":[112],"scene":[113],"geometry.":[114],"On":[115],"NeRF-Synthetic":[117],"benchmark,":[118],"inserting":[119],"12":[121,123],"X":[122],"pixel":[124],"increases":[126],"error":[128],"6.8x":[130],"LPIPS,":[132],"while":[133],"poisoned":[135],"remain":[137],"unobtrusive":[138],"human":[140],"viewers.":[141],"requires":[143],"no":[144],"pipeline":[145],"modifications,":[146],"offering":[147],"practical,":[149],"\"drop-in\"":[150],"preprocessing":[151],"step":[152],"for":[153],"content":[154],"creators":[155],"protect":[157],"their":[158],"data.":[160]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-17T00:00:00"}