{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:ZOJGTCLDJUDXNY7QZOJQM5KCFP","short_pith_number":"pith:ZOJGTCLD","schema_version":"1.0","canonical_sha256":"cb926989634d0776e3f0cb930675422bf1fa387afd3f7d84caeb7fd7f2c5116a","source":{"kind":"arxiv","id":"2411.10499","version":2},"attestation_state":"computed","paper":{"title":"FitDiT: Advancing the Authentic Garment Details for High-fidelity Virtual Try-on","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Boyuan Jiang, Chengjie Wang, Chengming Xu, Donghao Luo, Jiangning Zhang, Jinlong Peng, Qingdong He, Xiaobin Hu, Yanwei Fu, Yunsheng Wu","submitted_at":"2024-11-15T11:02:23Z","abstract_excerpt":"Although image-based virtual try-on has made considerable progress, emerging approaches still encounter challenges in producing high-fidelity and robust fitting images across diverse scenarios. These methods often struggle with issues such as texture-aware maintenance and size-aware fitting, which hinder their overall effectiveness. To address these limitations, we propose a novel garment perception enhancement technique, termed FitDiT, designed for high-fidelity virtual try-on using Diffusion Transformers (DiT) allocating more parameters and attention to high-resolution features. First, to fu"},"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":"2411.10499","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-15T11:02:23Z","cross_cats_sorted":[],"title_canon_sha256":"c0b40f8cf97b533791c75ca1899d58613352bfdfd2b5786e31034ff227ed1075","abstract_canon_sha256":"14167c6619c3945f606107310fde06005cf28deb9c55ca4e3a86261e4e95b1f4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:39:10.289576Z","signature_b64":"KGNj/R5zCFfMH1PbUsXz+zQpZn0ZJpAwkuJ35wmll3nuEnQVCtuTrSv/kG1JlTY+WuchLtqfZeIl+oqTuAL0CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cb926989634d0776e3f0cb930675422bf1fa387afd3f7d84caeb7fd7f2c5116a","last_reissued_at":"2026-07-05T09:39:10.289095Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:39:10.289095Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FitDiT: Advancing the Authentic Garment Details for High-fidelity Virtual Try-on","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Boyuan Jiang, Chengjie Wang, Chengming Xu, Donghao Luo, Jiangning Zhang, Jinlong Peng, Qingdong He, Xiaobin Hu, Yanwei Fu, Yunsheng Wu","submitted_at":"2024-11-15T11:02:23Z","abstract_excerpt":"Although image-based virtual try-on has made considerable progress, emerging approaches still encounter challenges in producing high-fidelity and robust fitting images across diverse scenarios. These methods often struggle with issues such as texture-aware maintenance and size-aware fitting, which hinder their overall effectiveness. To address these limitations, we propose a novel garment perception enhancement technique, termed FitDiT, designed for high-fidelity virtual try-on using Diffusion Transformers (DiT) allocating more parameters and attention to high-resolution features. First, to fu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.10499","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/2411.10499/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":"2411.10499","created_at":"2026-07-05T09:39:10.289151+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.10499v2","created_at":"2026-07-05T09:39:10.289151+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.10499","created_at":"2026-07-05T09:39:10.289151+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZOJGTCLDJUDX","created_at":"2026-07-05T09:39:10.289151+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZOJGTCLDJUDXNY7Q","created_at":"2026-07-05T09:39:10.289151+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZOJGTCLD","created_at":"2026-07-05T09:39:10.289151+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":7,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.12012","citing_title":"FitVTON: Fit-aware Virtual Try-On via Body-Garment Size Control","ref_index":17,"is_internal_anchor":false},{"citing_arxiv_id":"2606.27880","citing_title":"OrthoTryOn: Geometric Orthogonalization for Conflict-Free Unified Fashion Generation","ref_index":27,"is_internal_anchor":false},{"citing_arxiv_id":"2512.20340","citing_title":"The devil is in the details: Enhancing Video Virtual Try-On via Keyframe-Driven Details Injection","ref_index":17,"is_internal_anchor":false},{"citing_arxiv_id":"2605.12939","citing_title":"DirectTryOn: One-Step Virtual Try-On via Straightened Conditional Transport","ref_index":26,"is_internal_anchor":false},{"citing_arxiv_id":"2604.19748","citing_title":"Tstars-Tryon 1.0: Robust and Realistic Virtual Try-On for Diverse Fashion Items","ref_index":6,"is_internal_anchor":false},{"citing_arxiv_id":"2604.19748","citing_title":"Tstars-Tryon 1.0: Robust and Realistic Virtual Try-On for Diverse Fashion Items","ref_index":6,"is_internal_anchor":false},{"citing_arxiv_id":"2604.27958","citing_title":"TripVVT: A Large-Scale Triplet Dataset and a Coarse-Mask Baseline for In-the-Wild Video Virtual Try-On","ref_index":18,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZOJGTCLDJUDXNY7QZOJQM5KCFP","json":"https://pith.science/pith/ZOJGTCLDJUDXNY7QZOJQM5KCFP.json","graph_json":"https://pith.science/api/pith-number/ZOJGTCLDJUDXNY7QZOJQM5KCFP/graph.json","events_json":"https://pith.science/api/pith-number/ZOJGTCLDJUDXNY7QZOJQM5KCFP/events.json","paper":"https://pith.science/paper/ZOJGTCLD"},"agent_actions":{"view_html":"https://pith.science/pith/ZOJGTCLDJUDXNY7QZOJQM5KCFP","download_json":"https://pith.science/pith/ZOJGTCLDJUDXNY7QZOJQM5KCFP.json","view_paper":"https://pith.science/paper/ZOJGTCLD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.10499&json=true","fetch_graph":"https://pith.science/api/pith-number/ZOJGTCLDJUDXNY7QZOJQM5KCFP/graph.json","fetch_events":"https://pith.science/api/pith-number/ZOJGTCLDJUDXNY7QZOJQM5KCFP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZOJGTCLDJUDXNY7QZOJQM5KCFP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZOJGTCLDJUDXNY7QZOJQM5KCFP/action/storage_attestation","attest_author":"https://pith.science/pith/ZOJGTCLDJUDXNY7QZOJQM5KCFP/action/author_attestation","sign_citation":"https://pith.science/pith/ZOJGTCLDJUDXNY7QZOJQM5KCFP/action/citation_signature","submit_replication":"https://pith.science/pith/ZOJGTCLDJUDXNY7QZOJQM5KCFP/action/replication_record"}},"created_at":"2026-07-05T09:39:10.289151+00:00","updated_at":"2026-07-05T09:39:10.289151+00:00"}