{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:YIRUJCQPL5QMOGUXAO3WVQTRPB","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"1a078d75c791a0c10236a7acfde40648bfca89a7861213b9a69d318dfb7d8c2d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-14T16:11:42Z","title_canon_sha256":"f364ca6209b1ba6ad33ffd0dd7aff7c0e368efbf7b092cdae04f81322d20916b"},"schema_version":"1.0","source":{"id":"2312.09076","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.09076","created_at":"2026-07-13T01:17:35Z"},{"alias_kind":"arxiv_version","alias_value":"2312.09076v4","created_at":"2026-07-13T01:17:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.09076","created_at":"2026-07-13T01:17:35Z"},{"alias_kind":"pith_short_12","alias_value":"YIRUJCQPL5QM","created_at":"2026-07-13T01:17:35Z"},{"alias_kind":"pith_short_16","alias_value":"YIRUJCQPL5QMOGUX","created_at":"2026-07-13T01:17:35Z"},{"alias_kind":"pith_short_8","alias_value":"YIRUJCQP","created_at":"2026-07-13T01:17:35Z"}],"graph_snapshots":[{"event_id":"sha256:32ebef4080d0a048dcab31cb1089a874b37419db588bc31e59a458ac6f51aeac","target":"graph","created_at":"2026-07-13T01:17:35Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2312.09076/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Implicit neural representation has demonstrated promising results in 3D reconstruction on various scenes. However, existing approaches either struggle to model fast-moving objects or are incapable of handling large-scale camera ego-motions in urban environments. This leads to low-quality synthesized views of the large-scale urban scenes. In this paper, we aim to jointly solve the problems caused by large-scale scenes and fast-moving vehicles, which are more practical and challenging. To this end, we propose a progressive scene graph network architecture to learn the local scene representations","authors_text":"Chenpeng Su, Danwei Wang, Jingchuan Wang, Shao-Yuan Lo, Tianchen Deng, Weidong Chen, Yanbo Wang, Yejia Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-14T16:11:42Z","title":"ProSGNeRF: Progressive Dynamic Neural Scene Graph with Frequency Modulated Foundation Model in Urban Scenes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.09076","kind":"arxiv","version":4},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:96479efb80085a7a60e3453601de4b19540e8453149968ed0ca11d2f06ec7138","target":"record","created_at":"2026-07-13T01:17:35Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"1a078d75c791a0c10236a7acfde40648bfca89a7861213b9a69d318dfb7d8c2d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-14T16:11:42Z","title_canon_sha256":"f364ca6209b1ba6ad33ffd0dd7aff7c0e368efbf7b092cdae04f81322d20916b"},"schema_version":"1.0","source":{"id":"2312.09076","kind":"arxiv","version":4}},"canonical_sha256":"c223448a0f5f60c71a9703b76ac271786dc822a7e9b1d64e1cb8663cee40ee32","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c223448a0f5f60c71a9703b76ac271786dc822a7e9b1d64e1cb8663cee40ee32","first_computed_at":"2026-07-13T01:17:35.814734Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-13T01:17:35.814734Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6I9nzUex8B1eCRTOuowzYnlLgVt5fcsmSZZwchNa0jnRwyqhEeCUGNpkGTHE+l+7u2d8xCPN5abUAw9SPNZRBw==","signature_status":"signed_v1","signed_at":"2026-07-13T01:17:35.816074Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.09076","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:96479efb80085a7a60e3453601de4b19540e8453149968ed0ca11d2f06ec7138","sha256:32ebef4080d0a048dcab31cb1089a874b37419db588bc31e59a458ac6f51aeac"],"state_sha256":"e701954b61513bceaf88efd09c1d5b016fb50768ba690ef4e04a2eb015f5681a"}