{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:RWI7LIQKY2VMYX3B3DPV6UAFNR","short_pith_number":"pith:RWI7LIQK","schema_version":"1.0","canonical_sha256":"8d91f5a20ac6aacc5f61d8df5f50056c5fc90bb7a4c817f55481d0c2c908d589","source":{"kind":"arxiv","id":"2607.05389","version":1},"attestation_state":"computed","paper":{"title":"InFlux++: Real and Synthetic Data for Estimating Dynamic Camera Intrinsics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Benjamin Zhou, Caleb Kha-Uong, Chinmaya Saran, David W. Liu, Erich Liang, Jia Deng, Junhan Ouyang, Sreemanti Dey","submitted_at":"2026-07-06T17:58:33Z","abstract_excerpt":"Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms assume fixed intrinsics throughout a video, an assumption that often fails for real-world in-the-wild videos. Consequently, estimating per-frame intrinsics from RGB images is critical for making 3D methods robust to videos with dynamic intrinsics. InFlux previously advanced this research direction by establishing the first real-world benchmark with per-frame ground truth intrinsics for dynamic intrinsics videos. Nevertheless, existing methods remain inaccurate due to two obstacles: (i) training d"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.05389","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-06T17:58:33Z","cross_cats_sorted":[],"title_canon_sha256":"f15df4d32985a324c2bc2526077bd0bbe0a6f3fd3c3d6844c230a0b594a5bfa7","abstract_canon_sha256":"5b55e4231e6132a608fbe13b6b2afa02bb746e43b48c83cabace76c69189f909"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-07T03:19:25.789050Z","signature_b64":"D1xLgdib2q6WyW66nkLDu+E9cpjXGrnF1Qf5QVnwM1E1ejGr8ZsdftGyhPCmymKT12t6PUpl6s4xsD+Ru+G/Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8d91f5a20ac6aacc5f61d8df5f50056c5fc90bb7a4c817f55481d0c2c908d589","last_reissued_at":"2026-07-07T03:19:25.788559Z","signature_status":"signed_v1","first_computed_at":"2026-07-07T03:19:25.788559Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"InFlux++: Real and Synthetic Data for Estimating Dynamic Camera Intrinsics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Benjamin Zhou, Caleb Kha-Uong, Chinmaya Saran, David W. Liu, Erich Liang, Jia Deng, Junhan Ouyang, Sreemanti Dey","submitted_at":"2026-07-06T17:58:33Z","abstract_excerpt":"Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms assume fixed intrinsics throughout a video, an assumption that often fails for real-world in-the-wild videos. Consequently, estimating per-frame intrinsics from RGB images is critical for making 3D methods robust to videos with dynamic intrinsics. InFlux previously advanced this research direction by establishing the first real-world benchmark with per-frame ground truth intrinsics for dynamic intrinsics videos. Nevertheless, existing methods remain inaccurate due to two obstacles: (i) training d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.05389","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/2607.05389/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.05389","created_at":"2026-07-07T03:19:25.788618+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.05389v1","created_at":"2026-07-07T03:19:25.788618+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.05389","created_at":"2026-07-07T03:19:25.788618+00:00"},{"alias_kind":"pith_short_12","alias_value":"RWI7LIQKY2VM","created_at":"2026-07-07T03:19:25.788618+00:00"},{"alias_kind":"pith_short_16","alias_value":"RWI7LIQKY2VMYX3B","created_at":"2026-07-07T03:19:25.788618+00:00"},{"alias_kind":"pith_short_8","alias_value":"RWI7LIQK","created_at":"2026-07-07T03:19:25.788618+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RWI7LIQKY2VMYX3B3DPV6UAFNR","json":"https://pith.science/pith/RWI7LIQKY2VMYX3B3DPV6UAFNR.json","graph_json":"https://pith.science/api/pith-number/RWI7LIQKY2VMYX3B3DPV6UAFNR/graph.json","events_json":"https://pith.science/api/pith-number/RWI7LIQKY2VMYX3B3DPV6UAFNR/events.json","paper":"https://pith.science/paper/RWI7LIQK"},"agent_actions":{"view_html":"https://pith.science/pith/RWI7LIQKY2VMYX3B3DPV6UAFNR","download_json":"https://pith.science/pith/RWI7LIQKY2VMYX3B3DPV6UAFNR.json","view_paper":"https://pith.science/paper/RWI7LIQK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.05389&json=true","fetch_graph":"https://pith.science/api/pith-number/RWI7LIQKY2VMYX3B3DPV6UAFNR/graph.json","fetch_events":"https://pith.science/api/pith-number/RWI7LIQKY2VMYX3B3DPV6UAFNR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RWI7LIQKY2VMYX3B3DPV6UAFNR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RWI7LIQKY2VMYX3B3DPV6UAFNR/action/storage_attestation","attest_author":"https://pith.science/pith/RWI7LIQKY2VMYX3B3DPV6UAFNR/action/author_attestation","sign_citation":"https://pith.science/pith/RWI7LIQKY2VMYX3B3DPV6UAFNR/action/citation_signature","submit_replication":"https://pith.science/pith/RWI7LIQKY2VMYX3B3DPV6UAFNR/action/replication_record"}},"created_at":"2026-07-07T03:19:25.788618+00:00","updated_at":"2026-07-07T03:19:25.788618+00:00"}