{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:5VQ7GIDGBZIEAQNXP5PZOGY2PD","short_pith_number":"pith:5VQ7GIDG","schema_version":"1.0","canonical_sha256":"ed61f320660e504041b77f5f971b1a78fdbbb20c361ebb8cf14aa54f25e2e349","source":{"kind":"arxiv","id":"2507.06165","version":1},"attestation_state":"computed","paper":{"title":"OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ding Liang, Hao Xu, Xihui Liu, Yan-Pei Cao, Ying-Tian Liu, Yuan-Chen Guo, Yufan Zhou, Yukun Huang, Yunhan Yang, Zi-Xin Zou","submitted_at":"2025-07-08T16:46:15Z","abstract_excerpt":"The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, limiting their utility. We introduce OmniPart, a novel framework for part-aware 3D object generation designed to achieve high semantic decoupling among components while maintaining robust structural cohesion. OmniPart uniquely decouples this complex task into two synergistic stages: (1) an autoregressive structure planning module generates a controllable, variable-length sequence of 3D part bounding boxes, critically gu"},"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":"2507.06165","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-08T16:46:15Z","cross_cats_sorted":[],"title_canon_sha256":"bdc3c8f49e5c8a83ee8721a5ee93c4b5de2ca9fb1e9e8de034c5d4d2d03f2c1d","abstract_canon_sha256":"0698f2a43d32541a05326429cadd029ff75a60a0bf0a3b6b22d645cf89444657"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:33:53.196859Z","signature_b64":"Sj7cm2XQ3Qd73dymERSgloDAhNiQj0eO/BQ9cnJA7/jn2AiknbgBaHMRoulp9MmBKhanIukAHqAvFjD2Ie6VCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ed61f320660e504041b77f5f971b1a78fdbbb20c361ebb8cf14aa54f25e2e349","last_reissued_at":"2026-07-05T11:33:53.196380Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:33:53.196380Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ding Liang, Hao Xu, Xihui Liu, Yan-Pei Cao, Ying-Tian Liu, Yuan-Chen Guo, Yufan Zhou, Yukun Huang, Yunhan Yang, Zi-Xin Zou","submitted_at":"2025-07-08T16:46:15Z","abstract_excerpt":"The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, limiting their utility. We introduce OmniPart, a novel framework for part-aware 3D object generation designed to achieve high semantic decoupling among components while maintaining robust structural cohesion. OmniPart uniquely decouples this complex task into two synergistic stages: (1) an autoregressive structure planning module generates a controllable, variable-length sequence of 3D part bounding boxes, critically gu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.06165","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/2507.06165/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":"2507.06165","created_at":"2026-07-05T11:33:53.196439+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.06165v1","created_at":"2026-07-05T11:33:53.196439+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.06165","created_at":"2026-07-05T11:33:53.196439+00:00"},{"alias_kind":"pith_short_12","alias_value":"5VQ7GIDGBZIE","created_at":"2026-07-05T11:33:53.196439+00:00"},{"alias_kind":"pith_short_16","alias_value":"5VQ7GIDGBZIEAQNX","created_at":"2026-07-05T11:33:53.196439+00:00"},{"alias_kind":"pith_short_8","alias_value":"5VQ7GIDG","created_at":"2026-07-05T11:33:53.196439+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":5,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.23514","citing_title":"Arbor: Explicit Geometric Conditioning for Controllable 3D Asset Generation","ref_index":39,"is_internal_anchor":false},{"citing_arxiv_id":"2606.17520","citing_title":"GASE: Gaussian Splatting-Based Automated System for Reconstructing Embodied-Simulation Environments","ref_index":81,"is_internal_anchor":false},{"citing_arxiv_id":"2606.12099","citing_title":"ISAP-3D: Identity-Slot Aligned Part-Aware 3D Generation","ref_index":36,"is_internal_anchor":false},{"citing_arxiv_id":"2605.21572","citing_title":"PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects","ref_index":8,"is_internal_anchor":false},{"citing_arxiv_id":"2605.10922","citing_title":"Pixal3D: Pixel-Aligned 3D Generation from Images","ref_index":63,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5VQ7GIDGBZIEAQNXP5PZOGY2PD","json":"https://pith.science/pith/5VQ7GIDGBZIEAQNXP5PZOGY2PD.json","graph_json":"https://pith.science/api/pith-number/5VQ7GIDGBZIEAQNXP5PZOGY2PD/graph.json","events_json":"https://pith.science/api/pith-number/5VQ7GIDGBZIEAQNXP5PZOGY2PD/events.json","paper":"https://pith.science/paper/5VQ7GIDG"},"agent_actions":{"view_html":"https://pith.science/pith/5VQ7GIDGBZIEAQNXP5PZOGY2PD","download_json":"https://pith.science/pith/5VQ7GIDGBZIEAQNXP5PZOGY2PD.json","view_paper":"https://pith.science/paper/5VQ7GIDG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.06165&json=true","fetch_graph":"https://pith.science/api/pith-number/5VQ7GIDGBZIEAQNXP5PZOGY2PD/graph.json","fetch_events":"https://pith.science/api/pith-number/5VQ7GIDGBZIEAQNXP5PZOGY2PD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5VQ7GIDGBZIEAQNXP5PZOGY2PD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5VQ7GIDGBZIEAQNXP5PZOGY2PD/action/storage_attestation","attest_author":"https://pith.science/pith/5VQ7GIDGBZIEAQNXP5PZOGY2PD/action/author_attestation","sign_citation":"https://pith.science/pith/5VQ7GIDGBZIEAQNXP5PZOGY2PD/action/citation_signature","submit_replication":"https://pith.science/pith/5VQ7GIDGBZIEAQNXP5PZOGY2PD/action/replication_record"}},"created_at":"2026-07-05T11:33:53.196439+00:00","updated_at":"2026-07-05T11:33:53.196439+00:00"}