{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:YYGDGB7FUHOTQOMIVO4RJGHNYZ","short_pith_number":"pith:YYGDGB7F","canonical_record":{"source":{"id":"2409.06685","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-10T17:51:39Z","cross_cats_sorted":[],"title_canon_sha256":"911c1fb51a655fdb09a4d0b6566d42c349754573b0ec9a86858c1c2526628213","abstract_canon_sha256":"1343ad347b24bd808f51a4a23aeeb0aa7e86db9f1a70c0da96bb312bb4448bb6"},"schema_version":"1.0"},"canonical_sha256":"c60c3307e5a1dd383988abb91498edc66c60ba397a3cd25898f8666295532ac3","source":{"kind":"arxiv","id":"2409.06685","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.06685","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"arxiv_version","alias_value":"2409.06685v1","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.06685","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"pith_short_12","alias_value":"YYGDGB7FUHOT","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"pith_short_16","alias_value":"YYGDGB7FUHOTQOMI","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"pith_short_8","alias_value":"YYGDGB7F","created_at":"2026-07-05T09:05:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:YYGDGB7FUHOTQOMIVO4RJGHNYZ","target":"record","payload":{"canonical_record":{"source":{"id":"2409.06685","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-10T17:51:39Z","cross_cats_sorted":[],"title_canon_sha256":"911c1fb51a655fdb09a4d0b6566d42c349754573b0ec9a86858c1c2526628213","abstract_canon_sha256":"1343ad347b24bd808f51a4a23aeeb0aa7e86db9f1a70c0da96bb312bb4448bb6"},"schema_version":"1.0"},"canonical_sha256":"c60c3307e5a1dd383988abb91498edc66c60ba397a3cd25898f8666295532ac3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:05:28.086070Z","signature_b64":"IENC/Ffrewbf/52OfESupBIMQlBqsBHnHhCf65P2DSDc5AJYIIVfUAdU/td+j942HyVU5F50Ag7CENUL9g5fBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c60c3307e5a1dd383988abb91498edc66c60ba397a3cd25898f8666295532ac3","last_reissued_at":"2026-07-05T09:05:28.085571Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:05:28.085571Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.06685","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:05:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+5SJSGtTNU8wIovUG1LsQyCSB+ij/oA0W8gHRhXWYla4JCibNCZuYg7GhQRJLJPM+6uWAyeU8LotX1gDU5LJBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T02:44:28.263181Z"},"content_sha256":"058867615f5424c37aee0721b1012b4ab9f306e3c224eeea066a987067da976b","schema_version":"1.0","event_id":"sha256:058867615f5424c37aee0721b1012b4ab9f306e3c224eeea066a987067da976b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:YYGDGB7FUHOTQOMIVO4RJGHNYZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GigaGS: Scaling up Planar-Based 3D Gaussians for Large Scene Surface Reconstruction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Danpeng Chen, Di Huang, Guofeng Zhang, Junyi Chen, Tong He, Wanli Ouyang, Weicai Ye, Yifan Wang, Yu Qiao","submitted_at":"2024-09-10T17:51:39Z","abstract_excerpt":"3D Gaussian Splatting (3DGS) has shown promising performance in novel view synthesis. Previous methods adapt it to obtaining surfaces of either individual 3D objects or within limited scenes. In this paper, we make the first attempt to tackle the challenging task of large-scale scene surface reconstruction. This task is particularly difficult due to the high GPU memory consumption, different levels of details for geometric representation, and noticeable inconsistencies in appearance. To this end, we propose GigaGS, the first work for high-quality surface reconstruction for large-scale scenes u"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.06685","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/2409.06685/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:05:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PeFAzq+K9IE5nF8AZs6a1eaN/l7KtmVscV/7JoQmK8Js4UnV+YyZdT9Nd7iNhqKwAxScmpQBP6e+D/mZWrnyBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T02:44:28.263720Z"},"content_sha256":"29228f0e303afe1ec620b663a7a461470eb639806ed2afed0cf78119f652ec94","schema_version":"1.0","event_id":"sha256:29228f0e303afe1ec620b663a7a461470eb639806ed2afed0cf78119f652ec94"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YYGDGB7FUHOTQOMIVO4RJGHNYZ/bundle.json","state_url":"https://pith.science/pith/YYGDGB7FUHOTQOMIVO4RJGHNYZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YYGDGB7FUHOTQOMIVO4RJGHNYZ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-10T02:44:28Z","links":{"resolver":"https://pith.science/pith/YYGDGB7FUHOTQOMIVO4RJGHNYZ","bundle":"https://pith.science/pith/YYGDGB7FUHOTQOMIVO4RJGHNYZ/bundle.json","state":"https://pith.science/pith/YYGDGB7FUHOTQOMIVO4RJGHNYZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YYGDGB7FUHOTQOMIVO4RJGHNYZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YYGDGB7FUHOTQOMIVO4RJGHNYZ","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":"1343ad347b24bd808f51a4a23aeeb0aa7e86db9f1a70c0da96bb312bb4448bb6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-10T17:51:39Z","title_canon_sha256":"911c1fb51a655fdb09a4d0b6566d42c349754573b0ec9a86858c1c2526628213"},"schema_version":"1.0","source":{"id":"2409.06685","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.06685","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"arxiv_version","alias_value":"2409.06685v1","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.06685","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"pith_short_12","alias_value":"YYGDGB7FUHOT","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"pith_short_16","alias_value":"YYGDGB7FUHOTQOMI","created_at":"2026-07-05T09:05:28Z"},{"alias_kind":"pith_short_8","alias_value":"YYGDGB7F","created_at":"2026-07-05T09:05:28Z"}],"graph_snapshots":[{"event_id":"sha256:29228f0e303afe1ec620b663a7a461470eb639806ed2afed0cf78119f652ec94","target":"graph","created_at":"2026-07-05T09:05:28Z","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/2409.06685/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"3D Gaussian Splatting (3DGS) has shown promising performance in novel view synthesis. Previous methods adapt it to obtaining surfaces of either individual 3D objects or within limited scenes. In this paper, we make the first attempt to tackle the challenging task of large-scale scene surface reconstruction. This task is particularly difficult due to the high GPU memory consumption, different levels of details for geometric representation, and noticeable inconsistencies in appearance. To this end, we propose GigaGS, the first work for high-quality surface reconstruction for large-scale scenes u","authors_text":"Danpeng Chen, Di Huang, Guofeng Zhang, Junyi Chen, Tong He, Wanli Ouyang, Weicai Ye, Yifan Wang, Yu Qiao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-10T17:51:39Z","title":"GigaGS: Scaling up Planar-Based 3D Gaussians for Large Scene Surface Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.06685","kind":"arxiv","version":1},"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":"sha256:058867615f5424c37aee0721b1012b4ab9f306e3c224eeea066a987067da976b","target":"record","created_at":"2026-07-05T09:05:28Z","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":"1343ad347b24bd808f51a4a23aeeb0aa7e86db9f1a70c0da96bb312bb4448bb6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-10T17:51:39Z","title_canon_sha256":"911c1fb51a655fdb09a4d0b6566d42c349754573b0ec9a86858c1c2526628213"},"schema_version":"1.0","source":{"id":"2409.06685","kind":"arxiv","version":1}},"canonical_sha256":"c60c3307e5a1dd383988abb91498edc66c60ba397a3cd25898f8666295532ac3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c60c3307e5a1dd383988abb91498edc66c60ba397a3cd25898f8666295532ac3","first_computed_at":"2026-07-05T09:05:28.085571Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:05:28.085571Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IENC/Ffrewbf/52OfESupBIMQlBqsBHnHhCf65P2DSDc5AJYIIVfUAdU/td+j942HyVU5F50Ag7CENUL9g5fBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:05:28.086070Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.06685","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:058867615f5424c37aee0721b1012b4ab9f306e3c224eeea066a987067da976b","sha256:29228f0e303afe1ec620b663a7a461470eb639806ed2afed0cf78119f652ec94"],"state_sha256":"e8afa003c8d01fdef8856e21c9f6de1e17a835bf4910bb73bb6bd0faf6c741ce"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5fEob+mgYSRyzEiIBZ8vUaI2gAqBxC2EyIstPlV7odp2zoz8M4c0c9HJkAjN4yhM81QUhi5fZ3LrBzckHTjfCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T02:44:28.267126Z","bundle_sha256":"6891d9b08421f4539efcabfe9251726d9780ce803cfd16ddeaf951ac9862ec05"}}