{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:AISHCVBLR6NVN2KZ6CJXSSRPTP","short_pith_number":"pith:AISHCVBL","schema_version":"1.0","canonical_sha256":"022471542b8f9b56e959f093794a2f9bdd049c7709c0e0578a1b15d3109e5ae2","source":{"kind":"arxiv","id":"2405.07472","version":2},"attestation_state":"computed","paper":{"title":"GaussianVTON: 3D Human Virtual Try-ON via Multi-Stage Gaussian Splatting Editing with Image Prompting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dian Shao, Haodong Chen, Haojian Huang, Xiangsheng Ge, Yongle Huang","submitted_at":"2024-05-13T05:18:07Z","abstract_excerpt":"The increasing prominence of e-commerce has underscored the importance of Virtual Try-On (VTON). However, previous studies predominantly focus on the 2D realm and rely heavily on extensive data for training. Research on 3D VTON primarily centers on garment-body shape compatibility, a topic extensively covered in 2D VTON. Thanks to advances in 3D scene editing, a 2D diffusion model has now been adapted for 3D editing via multi-viewpoint editing. In this work, we propose GaussianVTON, an innovative 3D VTON pipeline integrating Gaussian Splatting (GS) editing with 2D VTON. To facilitate a seamles"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2405.07472","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-05-13T05:18:07Z","cross_cats_sorted":[],"title_canon_sha256":"7346c5df8f440705d19194c5483ab98df6f9da4dc5712cca04f2f3bedab36a99","abstract_canon_sha256":"4be10a2f3669b2e5fd908a40d1a86e10babfeaf9d5f817b9867d92d95747ad0d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:21:54.614260Z","signature_b64":"D0e9cYSxRmxsw2y76owRqc4yzES+6rdQiqRqryFRqcsW8aYpKs+EZdtrRHSkY4RGlDWituQXvJ7XjN5Gb9IAAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"022471542b8f9b56e959f093794a2f9bdd049c7709c0e0578a1b15d3109e5ae2","last_reissued_at":"2026-07-05T08:21:54.613861Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:21:54.613861Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GaussianVTON: 3D Human Virtual Try-ON via Multi-Stage Gaussian Splatting Editing with Image Prompting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dian Shao, Haodong Chen, Haojian Huang, Xiangsheng Ge, Yongle Huang","submitted_at":"2024-05-13T05:18:07Z","abstract_excerpt":"The increasing prominence of e-commerce has underscored the importance of Virtual Try-On (VTON). However, previous studies predominantly focus on the 2D realm and rely heavily on extensive data for training. Research on 3D VTON primarily centers on garment-body shape compatibility, a topic extensively covered in 2D VTON. Thanks to advances in 3D scene editing, a 2D diffusion model has now been adapted for 3D editing via multi-viewpoint editing. In this work, we propose GaussianVTON, an innovative 3D VTON pipeline integrating Gaussian Splatting (GS) editing with 2D VTON. To facilitate a seamles"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.07472","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2405.07472/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2405.07472","created_at":"2026-07-05T08:21:54.613917+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.07472v2","created_at":"2026-07-05T08:21:54.613917+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.07472","created_at":"2026-07-05T08:21:54.613917+00:00"},{"alias_kind":"pith_short_12","alias_value":"AISHCVBLR6NV","created_at":"2026-07-05T08:21:54.613917+00:00"},{"alias_kind":"pith_short_16","alias_value":"AISHCVBLR6NVN2KZ","created_at":"2026-07-05T08:21:54.613917+00:00"},{"alias_kind":"pith_short_8","alias_value":"AISHCVBL","created_at":"2026-07-05T08:21:54.613917+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.21001","citing_title":"DAMA: Disentangled Body-Anchored Gaussians for Controllable Multi-Layered Avatars","ref_index":7,"is_internal_anchor":false},{"citing_arxiv_id":"2508.09977","citing_title":"A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation","ref_index":155,"is_internal_anchor":false},{"citing_arxiv_id":"2604.02883","citing_title":"Information-Regularized Constrained Inversion for Stable Avatar Editing from Sparse Supervision","ref_index":5,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AISHCVBLR6NVN2KZ6CJXSSRPTP","json":"https://pith.science/pith/AISHCVBLR6NVN2KZ6CJXSSRPTP.json","graph_json":"https://pith.science/api/pith-number/AISHCVBLR6NVN2KZ6CJXSSRPTP/graph.json","events_json":"https://pith.science/api/pith-number/AISHCVBLR6NVN2KZ6CJXSSRPTP/events.json","paper":"https://pith.science/paper/AISHCVBL"},"agent_actions":{"view_html":"https://pith.science/pith/AISHCVBLR6NVN2KZ6CJXSSRPTP","download_json":"https://pith.science/pith/AISHCVBLR6NVN2KZ6CJXSSRPTP.json","view_paper":"https://pith.science/paper/AISHCVBL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.07472&json=true","fetch_graph":"https://pith.science/api/pith-number/AISHCVBLR6NVN2KZ6CJXSSRPTP/graph.json","fetch_events":"https://pith.science/api/pith-number/AISHCVBLR6NVN2KZ6CJXSSRPTP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AISHCVBLR6NVN2KZ6CJXSSRPTP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AISHCVBLR6NVN2KZ6CJXSSRPTP/action/storage_attestation","attest_author":"https://pith.science/pith/AISHCVBLR6NVN2KZ6CJXSSRPTP/action/author_attestation","sign_citation":"https://pith.science/pith/AISHCVBLR6NVN2KZ6CJXSSRPTP/action/citation_signature","submit_replication":"https://pith.science/pith/AISHCVBLR6NVN2KZ6CJXSSRPTP/action/replication_record"}},"created_at":"2026-07-05T08:21:54.613917+00:00","updated_at":"2026-07-05T08:21:54.613917+00:00"}