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dc.contributor.authorLewis, Ryan Hardesty
dc.date.accessioned2025-09-11T19:36:19Z
dc.date.available2025-09-11T19:36:19Z
dc.date.issued2025-08-10
dc.identifier.isbn979-8-4007-1550-1
dc.identifier.urihttps://hdl.handle.net/1721.1/162646
dc.descriptionSIGGRAPH Labs ’25, Vancouver, BC, Canadaen_US
dc.description.abstractMeshTorrent is a peer-to-peer platform for automated 3D content creation and exchange, inspired by BitTorrent-style file sharing. By merging AI-based text-to-3D generation with swarm-based distribution, MeshTorrent harnesses the combined bandwidth and storage resources of its users, enabling scalable and decentralized sharing of 3D assets. This paper describes the core design of MeshTorrent, including an AI workflow for generating fresh .glb files, metadata management via a distributed hash table, partial previews for quick inspection, and specialized extensions for 2D sprites (SpriteTorrent) and rigged character models (RigTorrent). Preliminary tests show faster content download times than single-host alternatives, reduced server costs, and robust resilience to network churn, advancing an open ecosystem for collaborative 3D model exchange.en_US
dc.publisherACM|Special Interest Group on Computer Graphics and Interactive Techniques Conference Labsen_US
dc.relation.isversionofhttps://doi.org/10.1145/3721251.3736272en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleMeshTorrent: A Community-Driven P2P System for AI-Generated 3D Model Creation and Distributionen_US
dc.typeArticleen_US
dc.identifier.citationRyan Hardesty Lewis. 2025. MeshTorrent: A Community-Driven P2P System for AI-Generated 3D Model Creation and Distribution. In Proceedings of the Special Interest Group on Computer Graphics and Interactive Techniques Conference Labs (SIGGRAPH Labs '25). Association for Computing Machinery, New York, NY, USA, Article 8, 1–2.en_US
dc.contributor.departmentMIT Institute for Data, Systems, and Societyen_US
dc.identifier.mitlicensePUBLISHER_POLICY
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2025-09-01T07:55:09Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2025-09-01T07:55:09Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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