{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:YZVERCHHZO5G5AMYKKQG2O4VZ2","short_pith_number":"pith:YZVERCHH","schema_version":"1.0","canonical_sha256":"c66a4888e7cbba6e819852a06d3b95ce9ccaa019921a480452284e12e71d2e97","source":{"kind":"arxiv","id":"2407.10923","version":1},"attestation_state":"computed","paper":{"title":"OPa-Ma: Text Guided Mamba for 360-degree Image Out-painting","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kai Yao, Penglei Gao, Steven Wang, Tiandi Ye, Xiaofeng Wang, Yuan Yao","submitted_at":"2024-07-15T17:23:00Z","abstract_excerpt":"In this paper, we tackle the recently popular topic of generating 360-degree images given the conventional narrow field of view (NFoV) images that could be taken from a single camera or cellphone. This task aims to predict the reasonable and consistent surroundings from the NFoV images. Existing methods for feature extraction and fusion, often built with transformer-based architectures, incur substantial memory usage and computational expense. They also have limitations in maintaining visual continuity across the entire 360-degree images, which could cause inconsistent texture and style genera"},"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":"2407.10923","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-15T17:23:00Z","cross_cats_sorted":[],"title_canon_sha256":"5babfb56ea4b7d29516519f8edc1e92dfee222c15ba132129b906ac94a5885b3","abstract_canon_sha256":"17751a3b088e700155e427c36630741909e4b1ac8e623f5f1db643a5fa5511f2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:44:06.203688Z","signature_b64":"7TT0X5M3Op1tbFEjbT75eRl49ZcbQVVlsxyMrxdtyDMif3xrvsBq6CWR/h3AD+ecpTjA2zTN1VznyPURifTTDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c66a4888e7cbba6e819852a06d3b95ce9ccaa019921a480452284e12e71d2e97","last_reissued_at":"2026-07-05T08:44:06.203211Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:44:06.203211Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"OPa-Ma: Text Guided Mamba for 360-degree Image Out-painting","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kai Yao, Penglei Gao, Steven Wang, Tiandi Ye, Xiaofeng Wang, Yuan Yao","submitted_at":"2024-07-15T17:23:00Z","abstract_excerpt":"In this paper, we tackle the recently popular topic of generating 360-degree images given the conventional narrow field of view (NFoV) images that could be taken from a single camera or cellphone. This task aims to predict the reasonable and consistent surroundings from the NFoV images. Existing methods for feature extraction and fusion, often built with transformer-based architectures, incur substantial memory usage and computational expense. They also have limitations in maintaining visual continuity across the entire 360-degree images, which could cause inconsistent texture and style genera"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.10923","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/2407.10923/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":"2407.10923","created_at":"2026-07-05T08:44:06.203268+00:00"},{"alias_kind":"arxiv_version","alias_value":"2407.10923v1","created_at":"2026-07-05T08:44:06.203268+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.10923","created_at":"2026-07-05T08:44:06.203268+00:00"},{"alias_kind":"pith_short_12","alias_value":"YZVERCHHZO5G","created_at":"2026-07-05T08:44:06.203268+00:00"},{"alias_kind":"pith_short_16","alias_value":"YZVERCHHZO5G5AMY","created_at":"2026-07-05T08:44:06.203268+00:00"},{"alias_kind":"pith_short_8","alias_value":"YZVERCHH","created_at":"2026-07-05T08:44:06.203268+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2603.28980","citing_title":"Stepper: Stepwise Immersive Scene Generation with Multiview Panoramas","ref_index":11,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YZVERCHHZO5G5AMYKKQG2O4VZ2","json":"https://pith.science/pith/YZVERCHHZO5G5AMYKKQG2O4VZ2.json","graph_json":"https://pith.science/api/pith-number/YZVERCHHZO5G5AMYKKQG2O4VZ2/graph.json","events_json":"https://pith.science/api/pith-number/YZVERCHHZO5G5AMYKKQG2O4VZ2/events.json","paper":"https://pith.science/paper/YZVERCHH"},"agent_actions":{"view_html":"https://pith.science/pith/YZVERCHHZO5G5AMYKKQG2O4VZ2","download_json":"https://pith.science/pith/YZVERCHHZO5G5AMYKKQG2O4VZ2.json","view_paper":"https://pith.science/paper/YZVERCHH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2407.10923&json=true","fetch_graph":"https://pith.science/api/pith-number/YZVERCHHZO5G5AMYKKQG2O4VZ2/graph.json","fetch_events":"https://pith.science/api/pith-number/YZVERCHHZO5G5AMYKKQG2O4VZ2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YZVERCHHZO5G5AMYKKQG2O4VZ2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YZVERCHHZO5G5AMYKKQG2O4VZ2/action/storage_attestation","attest_author":"https://pith.science/pith/YZVERCHHZO5G5AMYKKQG2O4VZ2/action/author_attestation","sign_citation":"https://pith.science/pith/YZVERCHHZO5G5AMYKKQG2O4VZ2/action/citation_signature","submit_replication":"https://pith.science/pith/YZVERCHHZO5G5AMYKKQG2O4VZ2/action/replication_record"}},"created_at":"2026-07-05T08:44:06.203268+00:00","updated_at":"2026-07-05T08:44:06.203268+00:00"}