{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:AMKZMQSBPDL3F6IA77V5KFTYZ5","short_pith_number":"pith:AMKZMQSB","canonical_record":{"source":{"id":"2404.12777","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-19T10:32:30Z","cross_cats_sorted":[],"title_canon_sha256":"0842d238e5905f7fe7bf756f8dbf11c7809a15d0fb9cf7def590e550081073cc","abstract_canon_sha256":"7d30576014854cd6d51243adfecc854c90dd7d4c3f11639e45ea66d8c5604507"},"schema_version":"1.0"},"canonical_sha256":"031596424178d7b2f900ffebd51678cf705081c1cf5990bf0e5671e819ed9bc7","source":{"kind":"arxiv","id":"2404.12777","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.12777","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"arxiv_version","alias_value":"2404.12777v1","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.12777","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"pith_short_12","alias_value":"AMKZMQSBPDL3","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"pith_short_16","alias_value":"AMKZMQSBPDL3F6IA","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"pith_short_8","alias_value":"AMKZMQSB","created_at":"2026-07-05T08:09:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:AMKZMQSBPDL3F6IA77V5KFTYZ5","target":"record","payload":{"canonical_record":{"source":{"id":"2404.12777","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-19T10:32:30Z","cross_cats_sorted":[],"title_canon_sha256":"0842d238e5905f7fe7bf756f8dbf11c7809a15d0fb9cf7def590e550081073cc","abstract_canon_sha256":"7d30576014854cd6d51243adfecc854c90dd7d4c3f11639e45ea66d8c5604507"},"schema_version":"1.0"},"canonical_sha256":"031596424178d7b2f900ffebd51678cf705081c1cf5990bf0e5671e819ed9bc7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:09:58.882231Z","signature_b64":"XldVuylZPBAaO5ORmlkceQyRXRPeQebZBoHBZdY2nV/c9hQmaZS2kWNaUhb9r88hslrFXU+tB1RoajU9myfcDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"031596424178d7b2f900ffebd51678cf705081c1cf5990bf0e5671e819ed9bc7","last_reissued_at":"2026-07-05T08:09:58.881752Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:09:58.881752Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.12777","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":"2026-07-05T08:09:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"85IHywWoHStsOK8ESZF1icSJK4D/uMRHEy3Wtly8CHNQXgvhS4m56d+9VcZAyR3X3fwUQksBObMVPyV2QP6JCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T22:45:40.992215Z"},"content_sha256":"10d8676ed6706d8258f346319c8b4aba21184543e469504381407dc718ee6eac","schema_version":"1.0","event_id":"sha256:10d8676ed6706d8258f346319c8b4aba21184543e469504381407dc718ee6eac"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:AMKZMQSBPDL3F6IA77V5KFTYZ5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EfficientGS: Streamlining Gaussian Splatting for Large-Scale High-Resolution Scene Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bin Zhu, Dan Li, Lili Ju, Tao Guan, Wei Yang, Wenkai Liu, Yuesong Wang, Zikai Song","submitted_at":"2024-04-19T10:32:30Z","abstract_excerpt":"In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\\times$4k pixels) is hindered by the excessive computational requirements for managing a large number of Gaussians. Addressing this, we introduce 'EfficientGS', an advanced approach that optimizes 3DGS for high-resolution, large-scale scenes. We analyze the densification process in 3DGS and identify areas of Gaussian over-proliferation. We propose a selective strategy, limiting Gaussian increase to key primitiv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.12777","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/2404.12777/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":"2026-07-05T08:09:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NFW3v3PBrIQC03meBw0Kr8oAeTtd5WOkqrSajWHONwaZQkwRhcmkEdvQBi6yW+CrzZ1XjI0EIrmKiRdlKVboBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T22:45:40.993183Z"},"content_sha256":"2c08be250ab7f1ebd8fb26fdbe8faf275e3b5331ed4122a0b33e4f8f2ea42443","schema_version":"1.0","event_id":"sha256:2c08be250ab7f1ebd8fb26fdbe8faf275e3b5331ed4122a0b33e4f8f2ea42443"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AMKZMQSBPDL3F6IA77V5KFTYZ5/bundle.json","state_url":"https://pith.science/pith/AMKZMQSBPDL3F6IA77V5KFTYZ5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AMKZMQSBPDL3F6IA77V5KFTYZ5/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":"2026-08-16T22:45:40Z","links":{"resolver":"https://pith.science/pith/AMKZMQSBPDL3F6IA77V5KFTYZ5","bundle":"https://pith.science/pith/AMKZMQSBPDL3F6IA77V5KFTYZ5/bundle.json","state":"https://pith.science/pith/AMKZMQSBPDL3F6IA77V5KFTYZ5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AMKZMQSBPDL3F6IA77V5KFTYZ5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:AMKZMQSBPDL3F6IA77V5KFTYZ5","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":"7d30576014854cd6d51243adfecc854c90dd7d4c3f11639e45ea66d8c5604507","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-19T10:32:30Z","title_canon_sha256":"0842d238e5905f7fe7bf756f8dbf11c7809a15d0fb9cf7def590e550081073cc"},"schema_version":"1.0","source":{"id":"2404.12777","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.12777","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"arxiv_version","alias_value":"2404.12777v1","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.12777","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"pith_short_12","alias_value":"AMKZMQSBPDL3","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"pith_short_16","alias_value":"AMKZMQSBPDL3F6IA","created_at":"2026-07-05T08:09:58Z"},{"alias_kind":"pith_short_8","alias_value":"AMKZMQSB","created_at":"2026-07-05T08:09:58Z"}],"graph_snapshots":[{"event_id":"sha256:2c08be250ab7f1ebd8fb26fdbe8faf275e3b5331ed4122a0b33e4f8f2ea42443","target":"graph","created_at":"2026-07-05T08:09:58Z","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/2404.12777/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\\times$4k pixels) is hindered by the excessive computational requirements for managing a large number of Gaussians. Addressing this, we introduce 'EfficientGS', an advanced approach that optimizes 3DGS for high-resolution, large-scale scenes. We analyze the densification process in 3DGS and identify areas of Gaussian over-proliferation. We propose a selective strategy, limiting Gaussian increase to key primitiv","authors_text":"Bin Zhu, Dan Li, Lili Ju, Tao Guan, Wei Yang, Wenkai Liu, Yuesong Wang, Zikai Song","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-19T10:32:30Z","title":"EfficientGS: Streamlining Gaussian Splatting for Large-Scale High-Resolution Scene Representation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.12777","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":"sha256:10d8676ed6706d8258f346319c8b4aba21184543e469504381407dc718ee6eac","target":"record","created_at":"2026-07-05T08:09:58Z","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":"7d30576014854cd6d51243adfecc854c90dd7d4c3f11639e45ea66d8c5604507","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-19T10:32:30Z","title_canon_sha256":"0842d238e5905f7fe7bf756f8dbf11c7809a15d0fb9cf7def590e550081073cc"},"schema_version":"1.0","source":{"id":"2404.12777","kind":"arxiv","version":1}},"canonical_sha256":"031596424178d7b2f900ffebd51678cf705081c1cf5990bf0e5671e819ed9bc7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"031596424178d7b2f900ffebd51678cf705081c1cf5990bf0e5671e819ed9bc7","first_computed_at":"2026-07-05T08:09:58.881752Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:09:58.881752Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XldVuylZPBAaO5ORmlkceQyRXRPeQebZBoHBZdY2nV/c9hQmaZS2kWNaUhb9r88hslrFXU+tB1RoajU9myfcDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:09:58.882231Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.12777","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:10d8676ed6706d8258f346319c8b4aba21184543e469504381407dc718ee6eac","sha256:2c08be250ab7f1ebd8fb26fdbe8faf275e3b5331ed4122a0b33e4f8f2ea42443"],"state_sha256":"281215638a8932396ca7a85fe4a3a7514a01c23bd62fb65a8fe274c710e5cd51"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XTn674vPTNGCNU5gfGyoHQ7sI073iwe3LZf68qtFHNhhTjmYk5+V2cCivanejXe3itdZQ+kMaLJ6otQ1N+sVCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T22:45:40.999311Z","bundle_sha256":"47a32801e515114094f863614fa86126ba24ad8c87a363aced145ccdd5f08c07"}}