{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:4FCTIMDUMVJZXYQZCTXFVIDQXP","short_pith_number":"pith:4FCTIMDU","schema_version":"1.0","canonical_sha256":"e14534307465539be21914ee5aa070bbdb58cd8813b9dba061659b2836bbeb05","source":{"kind":"arxiv","id":"2506.23607","version":1},"attestation_state":"computed","paper":{"title":"PGOV3D: Open-Vocabulary 3D Semantic Segmentation with Partial-to-Global Curriculum","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiajun Deng, Mingxiao Ma, Sha Zhang, Shiqi Zhang, Yanyong Zhang, Yedong Shen","submitted_at":"2025-06-30T08:13:07Z","abstract_excerpt":"Existing open-vocabulary 3D semantic segmentation methods typically supervise 3D segmentation models by merging text-aligned features (e.g., CLIP) extracted from multi-view images onto 3D points. However, such approaches treat multi-view images merely as intermediaries for transferring open-vocabulary information, overlooking their rich semantic content and cross-view correspondences, which limits model effectiveness. To address this, we propose PGOV3D, a novel framework that introduces a Partial-to-Global curriculum for improving open-vocabulary 3D semantic segmentation. The key innovation li"},"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":"2506.23607","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-30T08:13:07Z","cross_cats_sorted":[],"title_canon_sha256":"549df103424a85e740a072394b58fa2f4d0df0724ea1aec30cc7a4c5e7a2f9c5","abstract_canon_sha256":"4ff2ee33c475ec1662c796d7305f48026e96b9701e0cab8d758417b32a0b7172"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:29:24.785665Z","signature_b64":"De4rUjlqPWT1HR0CmINnHUOA9xbzgk8TwuvnL0AxiUlA74mMNZe+4uqPgHGbJ10Ip/ifbRYeme2v7+421dyuCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e14534307465539be21914ee5aa070bbdb58cd8813b9dba061659b2836bbeb05","last_reissued_at":"2026-07-05T11:29:24.785139Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:29:24.785139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"PGOV3D: Open-Vocabulary 3D Semantic Segmentation with Partial-to-Global Curriculum","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiajun Deng, Mingxiao Ma, Sha Zhang, Shiqi Zhang, Yanyong Zhang, Yedong Shen","submitted_at":"2025-06-30T08:13:07Z","abstract_excerpt":"Existing open-vocabulary 3D semantic segmentation methods typically supervise 3D segmentation models by merging text-aligned features (e.g., CLIP) extracted from multi-view images onto 3D points. However, such approaches treat multi-view images merely as intermediaries for transferring open-vocabulary information, overlooking their rich semantic content and cross-view correspondences, which limits model effectiveness. To address this, we propose PGOV3D, a novel framework that introduces a Partial-to-Global curriculum for improving open-vocabulary 3D semantic segmentation. The key innovation li"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.23607","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/2506.23607/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":"2506.23607","created_at":"2026-07-05T11:29:24.785198+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.23607v1","created_at":"2026-07-05T11:29:24.785198+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.23607","created_at":"2026-07-05T11:29:24.785198+00:00"},{"alias_kind":"pith_short_12","alias_value":"4FCTIMDUMVJZ","created_at":"2026-07-05T11:29:24.785198+00:00"},{"alias_kind":"pith_short_16","alias_value":"4FCTIMDUMVJZXYQZ","created_at":"2026-07-05T11:29:24.785198+00:00"},{"alias_kind":"pith_short_8","alias_value":"4FCTIMDU","created_at":"2026-07-05T11:29:24.785198+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/4FCTIMDUMVJZXYQZCTXFVIDQXP","json":"https://pith.science/pith/4FCTIMDUMVJZXYQZCTXFVIDQXP.json","graph_json":"https://pith.science/api/pith-number/4FCTIMDUMVJZXYQZCTXFVIDQXP/graph.json","events_json":"https://pith.science/api/pith-number/4FCTIMDUMVJZXYQZCTXFVIDQXP/events.json","paper":"https://pith.science/paper/4FCTIMDU"},"agent_actions":{"view_html":"https://pith.science/pith/4FCTIMDUMVJZXYQZCTXFVIDQXP","download_json":"https://pith.science/pith/4FCTIMDUMVJZXYQZCTXFVIDQXP.json","view_paper":"https://pith.science/paper/4FCTIMDU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.23607&json=true","fetch_graph":"https://pith.science/api/pith-number/4FCTIMDUMVJZXYQZCTXFVIDQXP/graph.json","fetch_events":"https://pith.science/api/pith-number/4FCTIMDUMVJZXYQZCTXFVIDQXP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4FCTIMDUMVJZXYQZCTXFVIDQXP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4FCTIMDUMVJZXYQZCTXFVIDQXP/action/storage_attestation","attest_author":"https://pith.science/pith/4FCTIMDUMVJZXYQZCTXFVIDQXP/action/author_attestation","sign_citation":"https://pith.science/pith/4FCTIMDUMVJZXYQZCTXFVIDQXP/action/citation_signature","submit_replication":"https://pith.science/pith/4FCTIMDUMVJZXYQZCTXFVIDQXP/action/replication_record"}},"created_at":"2026-07-05T11:29:24.785198+00:00","updated_at":"2026-07-05T11:29:24.785198+00:00"}