{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:7KPBYVZEOIO7JDICGPB3B6YJSB","short_pith_number":"pith:7KPBYVZE","canonical_record":{"source":{"id":"2211.14950","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-27T22:01:47Z","cross_cats_sorted":[],"title_canon_sha256":"13106e7a451b38aeca23e1b8ea93e585721260ede4c1c8b0809ba3dc8afbed32","abstract_canon_sha256":"3ea77c0a56d360ab6ba3ddcaa4ed58ab8cbc8722696ef7a9c8a410e4a97bee3a"},"schema_version":"1.0"},"canonical_sha256":"fa9e1c5724721df48d0233c3b0fb09905c165d3ebc33bb9a75484ef15934a866","source":{"kind":"arxiv","id":"2211.14950","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.14950","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"arxiv_version","alias_value":"2211.14950v2","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.14950","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"pith_short_12","alias_value":"7KPBYVZEOIO7","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"pith_short_16","alias_value":"7KPBYVZEOIO7JDIC","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"pith_short_8","alias_value":"7KPBYVZE","created_at":"2026-07-05T08:08:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:7KPBYVZEOIO7JDICGPB3B6YJSB","target":"record","payload":{"canonical_record":{"source":{"id":"2211.14950","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-27T22:01:47Z","cross_cats_sorted":[],"title_canon_sha256":"13106e7a451b38aeca23e1b8ea93e585721260ede4c1c8b0809ba3dc8afbed32","abstract_canon_sha256":"3ea77c0a56d360ab6ba3ddcaa4ed58ab8cbc8722696ef7a9c8a410e4a97bee3a"},"schema_version":"1.0"},"canonical_sha256":"fa9e1c5724721df48d0233c3b0fb09905c165d3ebc33bb9a75484ef15934a866","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:08:15.632727Z","signature_b64":"h5keCR18heBGEl/hfnTs7fe3s00wLsctyfaTjTllNkDpd5uL928HnlLIv3/Rh0fC097Mlf+/dAPTvNxLS2szAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa9e1c5724721df48d0233c3b0fb09905c165d3ebc33bb9a75484ef15934a866","last_reissued_at":"2026-07-05T08:08:15.632252Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:08:15.632252Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.14950","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":"2026-07-05T08:08:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7QAkt/9eJWzXTuEzs0P2yZRutp2739p01jiETS1Y0lXMGRLfJW1LA9eCIKRBBxKXF492jEGDcHZDWeNLlti4DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T12:38:09.919847Z"},"content_sha256":"44449bc665588360a384fc43c92126c960c71f2ad4e50ccc9c4737a9cf3d98d6","schema_version":"1.0","event_id":"sha256:44449bc665588360a384fc43c92126c960c71f2ad4e50ccc9c4737a9cf3d98d6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:7KPBYVZEOIO7JDICGPB3B6YJSB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Leveraging Image Matching Toward End-to-End Relative Camera Pose Regression","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fadi Khatib, Meirav Galun, Ronen Basri, Yuval Margalit","submitted_at":"2022-11-27T22:01:47Z","abstract_excerpt":"This paper proposes a generalizable, end-to-end deep learning-based method for relative pose regression between two images. Given two images of the same scene captured from different viewpoints, our method predicts the relative rotation and translation (including direction and scale) between the two respective cameras. Inspired by the classical pipeline, our method leverages Image Matching (IM) as a pre-trained task for relative pose regression. Specifically, we use LoFTR, an architecture that utilizes an attention-based network pre-trained on Scannet, to extract semi-dense feature maps, which"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.14950","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/2211.14950/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":"2026-07-05T08:08:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YADf+tYqVMTfQdsjnKD/cthuMeQaHX0sK+9wt+SBSxnzCz7d9GtlqwSH8rjSLMVpQpdSvcIKIyu2tVO0TkdXDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T12:38:09.920214Z"},"content_sha256":"8b6bbc0c819e4dba4b3f7f65258a5deeaf048a25f9e3826a70c85682e413d02a","schema_version":"1.0","event_id":"sha256:8b6bbc0c819e4dba4b3f7f65258a5deeaf048a25f9e3826a70c85682e413d02a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7KPBYVZEOIO7JDICGPB3B6YJSB/bundle.json","state_url":"https://pith.science/pith/7KPBYVZEOIO7JDICGPB3B6YJSB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7KPBYVZEOIO7JDICGPB3B6YJSB/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":"2026-07-06T12:38:09Z","links":{"resolver":"https://pith.science/pith/7KPBYVZEOIO7JDICGPB3B6YJSB","bundle":"https://pith.science/pith/7KPBYVZEOIO7JDICGPB3B6YJSB/bundle.json","state":"https://pith.science/pith/7KPBYVZEOIO7JDICGPB3B6YJSB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7KPBYVZEOIO7JDICGPB3B6YJSB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:7KPBYVZEOIO7JDICGPB3B6YJSB","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":"3ea77c0a56d360ab6ba3ddcaa4ed58ab8cbc8722696ef7a9c8a410e4a97bee3a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-27T22:01:47Z","title_canon_sha256":"13106e7a451b38aeca23e1b8ea93e585721260ede4c1c8b0809ba3dc8afbed32"},"schema_version":"1.0","source":{"id":"2211.14950","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.14950","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"arxiv_version","alias_value":"2211.14950v2","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.14950","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"pith_short_12","alias_value":"7KPBYVZEOIO7","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"pith_short_16","alias_value":"7KPBYVZEOIO7JDIC","created_at":"2026-07-05T08:08:15Z"},{"alias_kind":"pith_short_8","alias_value":"7KPBYVZE","created_at":"2026-07-05T08:08:15Z"}],"graph_snapshots":[{"event_id":"sha256:8b6bbc0c819e4dba4b3f7f65258a5deeaf048a25f9e3826a70c85682e413d02a","target":"graph","created_at":"2026-07-05T08:08:15Z","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/2211.14950/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper proposes a generalizable, end-to-end deep learning-based method for relative pose regression between two images. Given two images of the same scene captured from different viewpoints, our method predicts the relative rotation and translation (including direction and scale) between the two respective cameras. Inspired by the classical pipeline, our method leverages Image Matching (IM) as a pre-trained task for relative pose regression. Specifically, we use LoFTR, an architecture that utilizes an attention-based network pre-trained on Scannet, to extract semi-dense feature maps, which","authors_text":"Fadi Khatib, Meirav Galun, Ronen Basri, Yuval Margalit","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-27T22:01:47Z","title":"Leveraging Image Matching Toward End-to-End Relative Camera Pose Regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.14950","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":"sha256:44449bc665588360a384fc43c92126c960c71f2ad4e50ccc9c4737a9cf3d98d6","target":"record","created_at":"2026-07-05T08:08:15Z","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":"3ea77c0a56d360ab6ba3ddcaa4ed58ab8cbc8722696ef7a9c8a410e4a97bee3a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-27T22:01:47Z","title_canon_sha256":"13106e7a451b38aeca23e1b8ea93e585721260ede4c1c8b0809ba3dc8afbed32"},"schema_version":"1.0","source":{"id":"2211.14950","kind":"arxiv","version":2}},"canonical_sha256":"fa9e1c5724721df48d0233c3b0fb09905c165d3ebc33bb9a75484ef15934a866","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa9e1c5724721df48d0233c3b0fb09905c165d3ebc33bb9a75484ef15934a866","first_computed_at":"2026-07-05T08:08:15.632252Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:08:15.632252Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"h5keCR18heBGEl/hfnTs7fe3s00wLsctyfaTjTllNkDpd5uL928HnlLIv3/Rh0fC097Mlf+/dAPTvNxLS2szAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:08:15.632727Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.14950","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:44449bc665588360a384fc43c92126c960c71f2ad4e50ccc9c4737a9cf3d98d6","sha256:8b6bbc0c819e4dba4b3f7f65258a5deeaf048a25f9e3826a70c85682e413d02a"],"state_sha256":"22acb622eefe370490eab7533af60f8b06c2beb3e1d175bf91fc757eaa2a508b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DWE9geNwFoKBcaPgwYBSg+YgCfjBOL8vBt4OE5H/LSK78EZKOOmEgWU508lQaSQfz+R+4X+0eQhfeRNxBUf7BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T12:38:09.922342Z","bundle_sha256":"94a2d9835fe4069f5518074bd536cfd1d945c6187d11b7d237a2f6310a8cdcd9"}}