{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:E6RD57DYCK5H7XGW72AHSL5RLF","short_pith_number":"pith:E6RD57DY","schema_version":"1.0","canonical_sha256":"27a23efc7812ba7fdcd6fe80792fb15961ce82fcdc1bc5be4da92f5c80fe9e3f","source":{"kind":"arxiv","id":"2412.11457","version":2},"attestation_state":"computed","paper":{"title":"MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Baoxiong Jia, Diwen Wan, Gang Zeng, Junfeng Ni, Ruijie Lu, Siyuan Huang, Yixin Chen, Yu Liu","submitted_at":"2024-12-16T05:23:45Z","abstract_excerpt":"Repurposing pre-trained diffusion models has been proven to be effective for NVS. However, these methods are mostly limited to a single object; directly applying such methods to compositional multi-object scenarios yields inferior results, especially incorrect object placement and inconsistent shape and appearance under novel views. How to enhance and systematically evaluate the cross-view consistency of such models remains under-explored. To address this issue, we propose MOVIS to enhance the structural awareness of the view-conditioned diffusion model for multi-object NVS in terms of model i"},"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":"2412.11457","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-16T05:23:45Z","cross_cats_sorted":[],"title_canon_sha256":"e1af1d0dcdea12da5b38596306471f086ab22f2604665f061c0db3acb8075267","abstract_canon_sha256":"e59f0054b0a94e49a917f9d0478f6c7d056498681f12c1ff3a5f4e2cbef4c1aa"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:37:40.404869Z","signature_b64":"Y+1F6NXUAkhKecmPoMNCEQDqXJNKKT7Bzz4801B6AQFVGRVwv/xpoTu7bv2l3tzbexB1R9bbZk2pNyckgeP6Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27a23efc7812ba7fdcd6fe80792fb15961ce82fcdc1bc5be4da92f5c80fe9e3f","last_reissued_at":"2026-07-05T10:37:40.403840Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:37:40.403840Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Baoxiong Jia, Diwen Wan, Gang Zeng, Junfeng Ni, Ruijie Lu, Siyuan Huang, Yixin Chen, Yu Liu","submitted_at":"2024-12-16T05:23:45Z","abstract_excerpt":"Repurposing pre-trained diffusion models has been proven to be effective for NVS. However, these methods are mostly limited to a single object; directly applying such methods to compositional multi-object scenarios yields inferior results, especially incorrect object placement and inconsistent shape and appearance under novel views. How to enhance and systematically evaluate the cross-view consistency of such models remains under-explored. To address this issue, we propose MOVIS to enhance the structural awareness of the view-conditioned diffusion model for multi-object NVS in terms of model i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.11457","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/2412.11457/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":"2412.11457","created_at":"2026-07-05T10:37:40.403972+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.11457v2","created_at":"2026-07-05T10:37:40.403972+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.11457","created_at":"2026-07-05T10:37:40.403972+00:00"},{"alias_kind":"pith_short_12","alias_value":"E6RD57DYCK5H","created_at":"2026-07-05T10:37:40.403972+00:00"},{"alias_kind":"pith_short_16","alias_value":"E6RD57DYCK5H7XGW","created_at":"2026-07-05T10:37:40.403972+00:00"},{"alias_kind":"pith_short_8","alias_value":"E6RD57DY","created_at":"2026-07-05T10:37:40.403972+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/E6RD57DYCK5H7XGW72AHSL5RLF","json":"https://pith.science/pith/E6RD57DYCK5H7XGW72AHSL5RLF.json","graph_json":"https://pith.science/api/pith-number/E6RD57DYCK5H7XGW72AHSL5RLF/graph.json","events_json":"https://pith.science/api/pith-number/E6RD57DYCK5H7XGW72AHSL5RLF/events.json","paper":"https://pith.science/paper/E6RD57DY"},"agent_actions":{"view_html":"https://pith.science/pith/E6RD57DYCK5H7XGW72AHSL5RLF","download_json":"https://pith.science/pith/E6RD57DYCK5H7XGW72AHSL5RLF.json","view_paper":"https://pith.science/paper/E6RD57DY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.11457&json=true","fetch_graph":"https://pith.science/api/pith-number/E6RD57DYCK5H7XGW72AHSL5RLF/graph.json","fetch_events":"https://pith.science/api/pith-number/E6RD57DYCK5H7XGW72AHSL5RLF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/E6RD57DYCK5H7XGW72AHSL5RLF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/E6RD57DYCK5H7XGW72AHSL5RLF/action/storage_attestation","attest_author":"https://pith.science/pith/E6RD57DYCK5H7XGW72AHSL5RLF/action/author_attestation","sign_citation":"https://pith.science/pith/E6RD57DYCK5H7XGW72AHSL5RLF/action/citation_signature","submit_replication":"https://pith.science/pith/E6RD57DYCK5H7XGW72AHSL5RLF/action/replication_record"}},"created_at":"2026-07-05T10:37:40.403972+00:00","updated_at":"2026-07-05T10:37:40.403972+00:00"}