{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:P6R5TI7XIQ67EVSSVAKN2KCHXE","short_pith_number":"pith:P6R5TI7X","canonical_record":{"source":{"id":"2411.15482","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-23T07:39:30Z","cross_cats_sorted":[],"title_canon_sha256":"ede7ac58543fb587fe3d4bb10df62eaeb64ba18c021e483a00d4ba22a92f2121","abstract_canon_sha256":"62a7995d1e5050c138917118f5c92a18f42ae16c964db7cbc93917e9c089be42"},"schema_version":"1.0"},"canonical_sha256":"7fa3d9a3f7443df25652a814dd2847b9056fb5d01f2e0073f1ba84bbe901e5d2","source":{"kind":"arxiv","id":"2411.15482","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.15482","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"arxiv_version","alias_value":"2411.15482v2","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.15482","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_12","alias_value":"P6R5TI7XIQ67","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_16","alias_value":"P6R5TI7XIQ67EVSS","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_8","alias_value":"P6R5TI7X","created_at":"2026-07-05T10:39:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:P6R5TI7XIQ67EVSSVAKN2KCHXE","target":"record","payload":{"canonical_record":{"source":{"id":"2411.15482","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-23T07:39:30Z","cross_cats_sorted":[],"title_canon_sha256":"ede7ac58543fb587fe3d4bb10df62eaeb64ba18c021e483a00d4ba22a92f2121","abstract_canon_sha256":"62a7995d1e5050c138917118f5c92a18f42ae16c964db7cbc93917e9c089be42"},"schema_version":"1.0"},"canonical_sha256":"7fa3d9a3f7443df25652a814dd2847b9056fb5d01f2e0073f1ba84bbe901e5d2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:39:46.542682Z","signature_b64":"WKrBYNxIh6QtYGuKn6znvKlyfmbHjUildgW5WrtjFUKyPajTzOn0sqD+bUiqqO6kHg+DhxeowHC+E34wE4ihBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7fa3d9a3f7443df25652a814dd2847b9056fb5d01f2e0073f1ba84bbe901e5d2","last_reissued_at":"2026-07-05T10:39:46.542134Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:39:46.542134Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.15482","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:39:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y9IFdLscQyO0FfrEH+L1qdLkLE28SqPwDOQBvrI/sqI7AXuAPnC36TcwrrezwsCwGCMY4ObWPSWsX+btEsJZCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T06:56:24.880652Z"},"content_sha256":"5bd00ca12d0bff12271321ce8c37b4944827462ca29063378230823ce406b477","schema_version":"1.0","event_id":"sha256:5bd00ca12d0bff12271321ce8c37b4944827462ca29063378230823ce406b477"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:P6R5TI7XIQ67EVSSVAKN2KCHXE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SplatFlow: Self-Supervised Dynamic Gaussian Splatting in Neural Motion Flow Field for Autonomous Driving","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cheng Zhao, Mei Chen, Su Sun, Yingjie Victor Chen, Zhuoyang Sun","submitted_at":"2024-11-23T07:39:30Z","abstract_excerpt":"Most existing Dynamic Gaussian Splatting methods for complex dynamic urban scenarios rely on accurate object-level supervision from expensive manual labeling, limiting their scalability in real-world applications. In this paper, we introduce SplatFlow, a Self-Supervised Dynamic Gaussian Splatting within Neural Motion Flow Fields (NMFF) to learn 4D space-time representations without requiring tracked 3D bounding boxes, enabling accurate dynamic scene reconstruction and novel view RGB/depth/flow synthesis. SplatFlow designs a unified framework to seamlessly integrate time-dependent 4D Gaussian r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.15482","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/2411.15482/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":"2026-07-05T10:39:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sRBDMZOH+q3H7mvqO2LMlXirVLdOy+ijNIwHBVPHsL1Ir4TdPb6lF3iammSZqEQ+PXp3NMFTjrhdY6px/NT6Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T06:56:24.881152Z"},"content_sha256":"5e622104c22d04b477bec11e0dbfb704092ec3dce50c7df361a6c5f8cf53e903","schema_version":"1.0","event_id":"sha256:5e622104c22d04b477bec11e0dbfb704092ec3dce50c7df361a6c5f8cf53e903"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P6R5TI7XIQ67EVSSVAKN2KCHXE/bundle.json","state_url":"https://pith.science/pith/P6R5TI7XIQ67EVSSVAKN2KCHXE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P6R5TI7XIQ67EVSSVAKN2KCHXE/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":"2026-08-09T06:56:24Z","links":{"resolver":"https://pith.science/pith/P6R5TI7XIQ67EVSSVAKN2KCHXE","bundle":"https://pith.science/pith/P6R5TI7XIQ67EVSSVAKN2KCHXE/bundle.json","state":"https://pith.science/pith/P6R5TI7XIQ67EVSSVAKN2KCHXE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P6R5TI7XIQ67EVSSVAKN2KCHXE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:P6R5TI7XIQ67EVSSVAKN2KCHXE","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":"62a7995d1e5050c138917118f5c92a18f42ae16c964db7cbc93917e9c089be42","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-23T07:39:30Z","title_canon_sha256":"ede7ac58543fb587fe3d4bb10df62eaeb64ba18c021e483a00d4ba22a92f2121"},"schema_version":"1.0","source":{"id":"2411.15482","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.15482","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"arxiv_version","alias_value":"2411.15482v2","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.15482","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_12","alias_value":"P6R5TI7XIQ67","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_16","alias_value":"P6R5TI7XIQ67EVSS","created_at":"2026-07-05T10:39:46Z"},{"alias_kind":"pith_short_8","alias_value":"P6R5TI7X","created_at":"2026-07-05T10:39:46Z"}],"graph_snapshots":[{"event_id":"sha256:5e622104c22d04b477bec11e0dbfb704092ec3dce50c7df361a6c5f8cf53e903","target":"graph","created_at":"2026-07-05T10:39:46Z","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/2411.15482/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most existing Dynamic Gaussian Splatting methods for complex dynamic urban scenarios rely on accurate object-level supervision from expensive manual labeling, limiting their scalability in real-world applications. In this paper, we introduce SplatFlow, a Self-Supervised Dynamic Gaussian Splatting within Neural Motion Flow Fields (NMFF) to learn 4D space-time representations without requiring tracked 3D bounding boxes, enabling accurate dynamic scene reconstruction and novel view RGB/depth/flow synthesis. SplatFlow designs a unified framework to seamlessly integrate time-dependent 4D Gaussian r","authors_text":"Cheng Zhao, Mei Chen, Su Sun, Yingjie Victor Chen, Zhuoyang Sun","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-23T07:39:30Z","title":"SplatFlow: Self-Supervised Dynamic Gaussian Splatting in Neural Motion Flow Field for Autonomous Driving"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.15482","kind":"arxiv","version":2},"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":"sha256:5bd00ca12d0bff12271321ce8c37b4944827462ca29063378230823ce406b477","target":"record","created_at":"2026-07-05T10:39:46Z","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":"62a7995d1e5050c138917118f5c92a18f42ae16c964db7cbc93917e9c089be42","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-23T07:39:30Z","title_canon_sha256":"ede7ac58543fb587fe3d4bb10df62eaeb64ba18c021e483a00d4ba22a92f2121"},"schema_version":"1.0","source":{"id":"2411.15482","kind":"arxiv","version":2}},"canonical_sha256":"7fa3d9a3f7443df25652a814dd2847b9056fb5d01f2e0073f1ba84bbe901e5d2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7fa3d9a3f7443df25652a814dd2847b9056fb5d01f2e0073f1ba84bbe901e5d2","first_computed_at":"2026-07-05T10:39:46.542134Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:39:46.542134Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WKrBYNxIh6QtYGuKn6znvKlyfmbHjUildgW5WrtjFUKyPajTzOn0sqD+bUiqqO6kHg+DhxeowHC+E34wE4ihBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:39:46.542682Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.15482","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5bd00ca12d0bff12271321ce8c37b4944827462ca29063378230823ce406b477","sha256:5e622104c22d04b477bec11e0dbfb704092ec3dce50c7df361a6c5f8cf53e903"],"state_sha256":"b1ecb3251c7e3bc2197575430be087bebf04c8cdcc52bbf8aabec12592d27b75"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZA1JM8jcvjZVkZnjeemvETQTkyNT6f6/Wt+v5s1lbhnp+lh7CrlTjaFRT0tpTHfPJbFxL2ZoMKZ9UkNH51T8BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T06:56:24.886290Z","bundle_sha256":"1e3b828e60d022ca74673a3d0c7eea9aef789a65aade30ee9c4ea3d213dce410"}}