{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:IAGJ6AWMNOLSGOBJXJKZJSOI6O","short_pith_number":"pith:IAGJ6AWM","schema_version":"1.0","canonical_sha256":"400c9f02cc6b97233829ba5594c9c8f3935afa11ac10bdc53e9e042197d08a9c","source":{"kind":"arxiv","id":"2412.07237","version":3},"attestation_state":"computed","paper":{"title":"ArtFormer: Controllable Generation of Diverse 3D Articulated Objects","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.RO"],"primary_cat":"cs.CV","authors_text":"Botao Ren, Botian Xu, Jiayi Su, Jinhua Song, Yangfan He, Youhe Feng, Zheng Li","submitted_at":"2024-12-10T07:00:05Z","abstract_excerpt":"This paper presents a novel framework for modeling and conditional generation of 3D articulated objects. Troubled by flexibility-quality tradeoffs, existing methods are often limited to using predefined structures or retrieving shapes from static datasets. To address these challenges, we parameterize an articulated object as a tree of tokens and employ a transformer to generate both the object's high-level geometry code and its kinematic relations. Subsequently, each sub-part's geometry is further decoded using a signed-distance-function (SDF) shape prior, facilitating the synthesis of high-qu"},"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":"2412.07237","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-10T07:00:05Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"2883e688acf5edd6a94002d773b3f2f7717f95e0eb93a224a03231ece7c31c2e","abstract_canon_sha256":"e7500334a22475aac4d29778006a33dec69127bd9ec44447eaa1c8f96ff73057"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:43:41.789068Z","signature_b64":"upeOFPWM8WRCblcAztLWZV4lwX2XTdKNBVz7pVKNKeQt5BfCqoFPwqBp1+phl7/4RZgE/O+3VD7YEFYxBRoXAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"400c9f02cc6b97233829ba5594c9c8f3935afa11ac10bdc53e9e042197d08a9c","last_reissued_at":"2026-07-05T10:43:41.788577Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:43:41.788577Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ArtFormer: Controllable Generation of Diverse 3D Articulated Objects","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.RO"],"primary_cat":"cs.CV","authors_text":"Botao Ren, Botian Xu, Jiayi Su, Jinhua Song, Yangfan He, Youhe Feng, Zheng Li","submitted_at":"2024-12-10T07:00:05Z","abstract_excerpt":"This paper presents a novel framework for modeling and conditional generation of 3D articulated objects. Troubled by flexibility-quality tradeoffs, existing methods are often limited to using predefined structures or retrieving shapes from static datasets. To address these challenges, we parameterize an articulated object as a tree of tokens and employ a transformer to generate both the object's high-level geometry code and its kinematic relations. Subsequently, each sub-part's geometry is further decoded using a signed-distance-function (SDF) shape prior, facilitating the synthesis of high-qu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.07237","kind":"arxiv","version":3},"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/2412.07237/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":"2412.07237","created_at":"2026-07-05T10:43:41.788638+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.07237v3","created_at":"2026-07-05T10:43:41.788638+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.07237","created_at":"2026-07-05T10:43:41.788638+00:00"},{"alias_kind":"pith_short_12","alias_value":"IAGJ6AWMNOLS","created_at":"2026-07-05T10:43:41.788638+00:00"},{"alias_kind":"pith_short_16","alias_value":"IAGJ6AWMNOLSGOBJ","created_at":"2026-07-05T10:43:41.788638+00:00"},{"alias_kind":"pith_short_8","alias_value":"IAGJ6AWM","created_at":"2026-07-05T10:43:41.788638+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/IAGJ6AWMNOLSGOBJXJKZJSOI6O","json":"https://pith.science/pith/IAGJ6AWMNOLSGOBJXJKZJSOI6O.json","graph_json":"https://pith.science/api/pith-number/IAGJ6AWMNOLSGOBJXJKZJSOI6O/graph.json","events_json":"https://pith.science/api/pith-number/IAGJ6AWMNOLSGOBJXJKZJSOI6O/events.json","paper":"https://pith.science/paper/IAGJ6AWM"},"agent_actions":{"view_html":"https://pith.science/pith/IAGJ6AWMNOLSGOBJXJKZJSOI6O","download_json":"https://pith.science/pith/IAGJ6AWMNOLSGOBJXJKZJSOI6O.json","view_paper":"https://pith.science/paper/IAGJ6AWM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.07237&json=true","fetch_graph":"https://pith.science/api/pith-number/IAGJ6AWMNOLSGOBJXJKZJSOI6O/graph.json","fetch_events":"https://pith.science/api/pith-number/IAGJ6AWMNOLSGOBJXJKZJSOI6O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IAGJ6AWMNOLSGOBJXJKZJSOI6O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IAGJ6AWMNOLSGOBJXJKZJSOI6O/action/storage_attestation","attest_author":"https://pith.science/pith/IAGJ6AWMNOLSGOBJXJKZJSOI6O/action/author_attestation","sign_citation":"https://pith.science/pith/IAGJ6AWMNOLSGOBJXJKZJSOI6O/action/citation_signature","submit_replication":"https://pith.science/pith/IAGJ6AWMNOLSGOBJXJKZJSOI6O/action/replication_record"}},"created_at":"2026-07-05T10:43:41.788638+00:00","updated_at":"2026-07-05T10:43:41.788638+00:00"}