{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:OOTRB37UIQ7YN52N7ZCANAHCIR","short_pith_number":"pith:OOTRB37U","schema_version":"1.0","canonical_sha256":"73a710eff4443f86f74dfe440680e2445d6a56d0b373aa5649b8f3a4f1a6aeba","source":{"kind":"arxiv","id":"2606.29319","version":1},"attestation_state":"computed","paper":{"title":"FDM-MFVT: Few-step Sampling Diffusion Model for Mask-Free Virtual Try-On","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiaxin Liu, Jun Liu, Lai Jiang, Mai Xu, Xiaoye Liang","submitted_at":"2026-06-28T10:24:45Z","abstract_excerpt":"Image-based Virtual Try-On (IVTON) has greatly advanced through diffusion models, yet existing methods require many sampling steps and depend on masks with costly auxiliary networks. In addition, the absence of large-scale mask-free paired datasets further limits the development of mask-free IVTON. We propose FDM-MFVT, a few-step diffusion model for mask-free IVTON, integrating an Outfit-aware Noise Optimization Module (OANO) and an Instruction-driven Try-on Module (IDT) to enhance efficiency and flexibility.The OANO module initializes the alignment space with noise using the input image and o"},"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":"2606.29319","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-28T10:24:45Z","cross_cats_sorted":[],"title_canon_sha256":"2bf695ce5a7fff7264f1f446e7b98b2912d1d35added433d799df876bb7c081a","abstract_canon_sha256":"6f326bfa298d989e742ccaa8364a8c44e0bbf66766e4c05e4c5f65ad2356187c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T01:18:01.347600Z","signature_b64":"iVVBL7g2ynaugz6n0GLlEPwboqpTnCGWQg+UqnYKB/XPyQfjcVuah4RudguQTt5XR9DNyMTOHWe6DZRNI5HvBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"73a710eff4443f86f74dfe440680e2445d6a56d0b373aa5649b8f3a4f1a6aeba","last_reissued_at":"2026-06-30T01:18:01.346769Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T01:18:01.346769Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FDM-MFVT: Few-step Sampling Diffusion Model for Mask-Free Virtual Try-On","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiaxin Liu, Jun Liu, Lai Jiang, Mai Xu, Xiaoye Liang","submitted_at":"2026-06-28T10:24:45Z","abstract_excerpt":"Image-based Virtual Try-On (IVTON) has greatly advanced through diffusion models, yet existing methods require many sampling steps and depend on masks with costly auxiliary networks. In addition, the absence of large-scale mask-free paired datasets further limits the development of mask-free IVTON. We propose FDM-MFVT, a few-step diffusion model for mask-free IVTON, integrating an Outfit-aware Noise Optimization Module (OANO) and an Instruction-driven Try-on Module (IDT) to enhance efficiency and flexibility.The OANO module initializes the alignment space with noise using the input image and o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.29319","kind":"arxiv","version":1},"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/2606.29319/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":"2606.29319","created_at":"2026-06-30T01:18:01.346887+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.29319v1","created_at":"2026-06-30T01:18:01.346887+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.29319","created_at":"2026-06-30T01:18:01.346887+00:00"},{"alias_kind":"pith_short_12","alias_value":"OOTRB37UIQ7Y","created_at":"2026-06-30T01:18:01.346887+00:00"},{"alias_kind":"pith_short_16","alias_value":"OOTRB37UIQ7YN52N","created_at":"2026-06-30T01:18:01.346887+00:00"},{"alias_kind":"pith_short_8","alias_value":"OOTRB37U","created_at":"2026-06-30T01:18:01.346887+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OOTRB37UIQ7YN52N7ZCANAHCIR","json":"https://pith.science/pith/OOTRB37UIQ7YN52N7ZCANAHCIR.json","graph_json":"https://pith.science/api/pith-number/OOTRB37UIQ7YN52N7ZCANAHCIR/graph.json","events_json":"https://pith.science/api/pith-number/OOTRB37UIQ7YN52N7ZCANAHCIR/events.json","paper":"https://pith.science/paper/OOTRB37U"},"agent_actions":{"view_html":"https://pith.science/pith/OOTRB37UIQ7YN52N7ZCANAHCIR","download_json":"https://pith.science/pith/OOTRB37UIQ7YN52N7ZCANAHCIR.json","view_paper":"https://pith.science/paper/OOTRB37U","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.29319&json=true","fetch_graph":"https://pith.science/api/pith-number/OOTRB37UIQ7YN52N7ZCANAHCIR/graph.json","fetch_events":"https://pith.science/api/pith-number/OOTRB37UIQ7YN52N7ZCANAHCIR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OOTRB37UIQ7YN52N7ZCANAHCIR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OOTRB37UIQ7YN52N7ZCANAHCIR/action/storage_attestation","attest_author":"https://pith.science/pith/OOTRB37UIQ7YN52N7ZCANAHCIR/action/author_attestation","sign_citation":"https://pith.science/pith/OOTRB37UIQ7YN52N7ZCANAHCIR/action/citation_signature","submit_replication":"https://pith.science/pith/OOTRB37UIQ7YN52N7ZCANAHCIR/action/replication_record"}},"created_at":"2026-06-30T01:18:01.346887+00:00","updated_at":"2026-06-30T01:18:01.346887+00:00"}