{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:X27DBQV5XULGER66ISZQHXESQJ","short_pith_number":"pith:X27DBQV5","canonical_record":{"source":{"id":"2306.00180","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-31T20:58:46Z","cross_cats_sorted":["cs.AI","cs.GR","cs.LG"],"title_canon_sha256":"c293eba691b30ed043883c0f5e4a7cea4412a0d0012f86b069e92ec2978082f9","abstract_canon_sha256":"5e822e2314726923aa9c22c9b4970cd61611e04c4bc143a7a2f91b90522f86e6"},"schema_version":"1.0"},"canonical_sha256":"bebe30c2bdbd166247de44b303dc92827c8d43feeb204a60ba4cd5a48eb1d747","source":{"kind":"arxiv","id":"2306.00180","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.00180","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"arxiv_version","alias_value":"2306.00180v1","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.00180","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"pith_short_12","alias_value":"X27DBQV5XULG","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"pith_short_16","alias_value":"X27DBQV5XULGER66","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"pith_short_8","alias_value":"X27DBQV5","created_at":"2026-07-05T06:16:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:X27DBQV5XULGER66ISZQHXESQJ","target":"record","payload":{"canonical_record":{"source":{"id":"2306.00180","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-31T20:58:46Z","cross_cats_sorted":["cs.AI","cs.GR","cs.LG"],"title_canon_sha256":"c293eba691b30ed043883c0f5e4a7cea4412a0d0012f86b069e92ec2978082f9","abstract_canon_sha256":"5e822e2314726923aa9c22c9b4970cd61611e04c4bc143a7a2f91b90522f86e6"},"schema_version":"1.0"},"canonical_sha256":"bebe30c2bdbd166247de44b303dc92827c8d43feeb204a60ba4cd5a48eb1d747","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:16:23.116269Z","signature_b64":"R2UWuJ+/mupSYTjuNRjU2VemFd88wuj6hrrtMX7sdbyOXPVj2ODRsXu32Ad2A+80R7VtoV4F6fmUMWGbnpG3DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bebe30c2bdbd166247de44b303dc92827c8d43feeb204a60ba4cd5a48eb1d747","last_reissued_at":"2026-07-05T06:16:23.115761Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:16:23.115761Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.00180","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":"2026-07-05T06:16:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cXfJU2Ex299zFr3TpChtQ2affQnOTkn5uA1b28pUaihOfQT3uWGHkM7ulQEAoomljgRiNXoSVaksEpEACkkcDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T11:41:18.126006Z"},"content_sha256":"580adebe16959950c7b5f6841675e3a2c4cf2697c9f05b24028bb1ca78783db0","schema_version":"1.0","event_id":"sha256:580adebe16959950c7b5f6841675e3a2c4cf2697c9f05b24028bb1ca78783db0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:X27DBQV5XULGER66ISZQHXESQJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.GR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Ayush Tewari, Cameron Smith, Vincent Sitzmann, Yilun Du","submitted_at":"2023-05-31T20:58:46Z","abstract_excerpt":"Reconstruction of 3D neural fields from posed images has emerged as a promising method for self-supervised representation learning. The key challenge preventing the deployment of these 3D scene learners on large-scale video data is their dependence on precise camera poses from structure-from-motion, which is prohibitively expensive to run at scale. We propose a method that jointly reconstructs camera poses and 3D neural scene representations online and in a single forward pass. We estimate poses by first lifting frame-to-frame optical flow to 3D scene flow via differentiable rendering, preserv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.00180","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/2306.00180/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":"2026-07-05T06:16:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5nxwGofsrX79+FC5LpEbfTqUpMHpHOforhMgP8dDCkWq0JmzgqyDbilHuu2P+mvTTLMxC3LnDBrXpnqWKswJAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T11:41:18.126520Z"},"content_sha256":"48991205530250e0b31a8559f7334ac9887882f66209e2a57e5da119d297cfdb","schema_version":"1.0","event_id":"sha256:48991205530250e0b31a8559f7334ac9887882f66209e2a57e5da119d297cfdb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X27DBQV5XULGER66ISZQHXESQJ/bundle.json","state_url":"https://pith.science/pith/X27DBQV5XULGER66ISZQHXESQJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X27DBQV5XULGER66ISZQHXESQJ/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":"2026-08-13T11:41:18Z","links":{"resolver":"https://pith.science/pith/X27DBQV5XULGER66ISZQHXESQJ","bundle":"https://pith.science/pith/X27DBQV5XULGER66ISZQHXESQJ/bundle.json","state":"https://pith.science/pith/X27DBQV5XULGER66ISZQHXESQJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X27DBQV5XULGER66ISZQHXESQJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:X27DBQV5XULGER66ISZQHXESQJ","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":"5e822e2314726923aa9c22c9b4970cd61611e04c4bc143a7a2f91b90522f86e6","cross_cats_sorted":["cs.AI","cs.GR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-31T20:58:46Z","title_canon_sha256":"c293eba691b30ed043883c0f5e4a7cea4412a0d0012f86b069e92ec2978082f9"},"schema_version":"1.0","source":{"id":"2306.00180","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.00180","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"arxiv_version","alias_value":"2306.00180v1","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.00180","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"pith_short_12","alias_value":"X27DBQV5XULG","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"pith_short_16","alias_value":"X27DBQV5XULGER66","created_at":"2026-07-05T06:16:23Z"},{"alias_kind":"pith_short_8","alias_value":"X27DBQV5","created_at":"2026-07-05T06:16:23Z"}],"graph_snapshots":[{"event_id":"sha256:48991205530250e0b31a8559f7334ac9887882f66209e2a57e5da119d297cfdb","target":"graph","created_at":"2026-07-05T06:16:23Z","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/2306.00180/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reconstruction of 3D neural fields from posed images has emerged as a promising method for self-supervised representation learning. The key challenge preventing the deployment of these 3D scene learners on large-scale video data is their dependence on precise camera poses from structure-from-motion, which is prohibitively expensive to run at scale. We propose a method that jointly reconstructs camera poses and 3D neural scene representations online and in a single forward pass. We estimate poses by first lifting frame-to-frame optical flow to 3D scene flow via differentiable rendering, preserv","authors_text":"Ayush Tewari, Cameron Smith, Vincent Sitzmann, Yilun Du","cross_cats":["cs.AI","cs.GR","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-31T20:58:46Z","title":"FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.00180","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":"sha256:580adebe16959950c7b5f6841675e3a2c4cf2697c9f05b24028bb1ca78783db0","target":"record","created_at":"2026-07-05T06:16:23Z","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":"5e822e2314726923aa9c22c9b4970cd61611e04c4bc143a7a2f91b90522f86e6","cross_cats_sorted":["cs.AI","cs.GR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-31T20:58:46Z","title_canon_sha256":"c293eba691b30ed043883c0f5e4a7cea4412a0d0012f86b069e92ec2978082f9"},"schema_version":"1.0","source":{"id":"2306.00180","kind":"arxiv","version":1}},"canonical_sha256":"bebe30c2bdbd166247de44b303dc92827c8d43feeb204a60ba4cd5a48eb1d747","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bebe30c2bdbd166247de44b303dc92827c8d43feeb204a60ba4cd5a48eb1d747","first_computed_at":"2026-07-05T06:16:23.115761Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:16:23.115761Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"R2UWuJ+/mupSYTjuNRjU2VemFd88wuj6hrrtMX7sdbyOXPVj2ODRsXu32Ad2A+80R7VtoV4F6fmUMWGbnpG3DA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:16:23.116269Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.00180","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:580adebe16959950c7b5f6841675e3a2c4cf2697c9f05b24028bb1ca78783db0","sha256:48991205530250e0b31a8559f7334ac9887882f66209e2a57e5da119d297cfdb"],"state_sha256":"97b0b34930e2b2d9cacba05d546ed4889c1a9a904c3fe21674360a4401388217"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L5kk0Jp1bzUSe9tW0I/X68n+4JUmwVSrnhdYkoWl2msNpXSbg7PP3QE1hjRAHkWePVhjcOt6+/ZcQdSnkdCFBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T11:41:18.155260Z","bundle_sha256":"4b32f45e65ab55e29654d9a697cda49a453be3a8fb2e1deb4412207747caa80e"}}