{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:IXFKBR5MXZEHOYSLZJJL7DU6TA","short_pith_number":"pith:IXFKBR5M","canonical_record":{"source":{"id":"2111.11141","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-22T12:05:27Z","cross_cats_sorted":[],"title_canon_sha256":"1e10f3ddd188734d463745a51f327276d56fb9ae4a269add75498531fa112ebc","abstract_canon_sha256":"6d7415570ff7dc17a8704f781e4f10df6cdc7a049498d96622e693e3cb7fcb77"},"schema_version":"1.0"},"canonical_sha256":"45caa0c7acbe4877624bca52bf8e9e98068e25cb35866675a891be97627235c1","source":{"kind":"arxiv","id":"2111.11141","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.11141","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"arxiv_version","alias_value":"2111.11141v2","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.11141","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"pith_short_12","alias_value":"IXFKBR5MXZEH","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"pith_short_16","alias_value":"IXFKBR5MXZEHOYSL","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"pith_short_8","alias_value":"IXFKBR5M","created_at":"2026-07-05T05:27:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:IXFKBR5MXZEHOYSLZJJL7DU6TA","target":"record","payload":{"canonical_record":{"source":{"id":"2111.11141","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-22T12:05:27Z","cross_cats_sorted":[],"title_canon_sha256":"1e10f3ddd188734d463745a51f327276d56fb9ae4a269add75498531fa112ebc","abstract_canon_sha256":"6d7415570ff7dc17a8704f781e4f10df6cdc7a049498d96622e693e3cb7fcb77"},"schema_version":"1.0"},"canonical_sha256":"45caa0c7acbe4877624bca52bf8e9e98068e25cb35866675a891be97627235c1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:27:16.583350Z","signature_b64":"V6T2ZPNdfQ3AXRXiZGqggnRq5c6rza8RhUyhpfHdEvYkYDOuEkJIcQK8ODvLDb2mupPAySt/q5bfW1w7gPg6Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"45caa0c7acbe4877624bca52bf8e9e98068e25cb35866675a891be97627235c1","last_reissued_at":"2026-07-05T05:27:16.582893Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:27:16.582893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2111.11141","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":"2026-07-05T05:27:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0a0OeXEjl7CCOnAnzwIgowNXoT6/PJF7arz55kIkQ3fCuK+Xy0MAaGD3XL3CxgDzog/gN69gEvZDkQ03ggJPCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:59:30.638539Z"},"content_sha256":"e5c801520f4042b3242c9d82259b9e94c4a011d1aa625ea4ebcc53d759bd9d08","schema_version":"1.0","event_id":"sha256:e5c801520f4042b3242c9d82259b9e94c4a011d1aa625ea4ebcc53d759bd9d08"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:IXFKBR5MXZEHOYSLZJJL7DU6TA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fuya Luo, Peng Peng, Xianshi Zhang, Yijun Cao, Yongjie Li","submitted_at":"2021-11-22T12:05:27Z","abstract_excerpt":"Recent visual odometry (VO) methods incorporating geometric algorithm into deep-learning architecture have shown outstanding performance on the challenging monocular VO task. Despite encouraging results are shown, previous methods ignore the requirement of generalization capability under noisy environment and various scenes. To address this challenging issue, this work first proposes a novel optical flow network (PANet). Compared with previous methods that predict optical flow as a direct regression task, our PANet computes optical flow by predicting it into the discrete position space with op"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.11141","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/2111.11141/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":"2026-07-05T05:27:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iZ3RBQJEBlYLNENBk45nVe94TH+BkY9LxWmSH+U3gz1y6+J/fvCdx9kzk6ORrGMMKSR6FGHN9N//11ci1HIJAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:59:30.638917Z"},"content_sha256":"4924b0dfb424aab6e10434068273b0f73394e3dd1ae7b674fbe660761b2b6b34","schema_version":"1.0","event_id":"sha256:4924b0dfb424aab6e10434068273b0f73394e3dd1ae7b674fbe660761b2b6b34"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IXFKBR5MXZEHOYSLZJJL7DU6TA/bundle.json","state_url":"https://pith.science/pith/IXFKBR5MXZEHOYSLZJJL7DU6TA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IXFKBR5MXZEHOYSLZJJL7DU6TA/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":"2026-07-05T15:59:30Z","links":{"resolver":"https://pith.science/pith/IXFKBR5MXZEHOYSLZJJL7DU6TA","bundle":"https://pith.science/pith/IXFKBR5MXZEHOYSLZJJL7DU6TA/bundle.json","state":"https://pith.science/pith/IXFKBR5MXZEHOYSLZJJL7DU6TA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IXFKBR5MXZEHOYSLZJJL7DU6TA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:IXFKBR5MXZEHOYSLZJJL7DU6TA","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":"6d7415570ff7dc17a8704f781e4f10df6cdc7a049498d96622e693e3cb7fcb77","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-22T12:05:27Z","title_canon_sha256":"1e10f3ddd188734d463745a51f327276d56fb9ae4a269add75498531fa112ebc"},"schema_version":"1.0","source":{"id":"2111.11141","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.11141","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"arxiv_version","alias_value":"2111.11141v2","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.11141","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"pith_short_12","alias_value":"IXFKBR5MXZEH","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"pith_short_16","alias_value":"IXFKBR5MXZEHOYSL","created_at":"2026-07-05T05:27:16Z"},{"alias_kind":"pith_short_8","alias_value":"IXFKBR5M","created_at":"2026-07-05T05:27:16Z"}],"graph_snapshots":[{"event_id":"sha256:4924b0dfb424aab6e10434068273b0f73394e3dd1ae7b674fbe660761b2b6b34","target":"graph","created_at":"2026-07-05T05:27:16Z","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/2111.11141/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent visual odometry (VO) methods incorporating geometric algorithm into deep-learning architecture have shown outstanding performance on the challenging monocular VO task. Despite encouraging results are shown, previous methods ignore the requirement of generalization capability under noisy environment and various scenes. To address this challenging issue, this work first proposes a novel optical flow network (PANet). Compared with previous methods that predict optical flow as a direct regression task, our PANet computes optical flow by predicting it into the discrete position space with op","authors_text":"Fuya Luo, Peng Peng, Xianshi Zhang, Yijun Cao, Yongjie Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-22T12:05:27Z","title":"Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.11141","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:e5c801520f4042b3242c9d82259b9e94c4a011d1aa625ea4ebcc53d759bd9d08","target":"record","created_at":"2026-07-05T05:27:16Z","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":"6d7415570ff7dc17a8704f781e4f10df6cdc7a049498d96622e693e3cb7fcb77","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-22T12:05:27Z","title_canon_sha256":"1e10f3ddd188734d463745a51f327276d56fb9ae4a269add75498531fa112ebc"},"schema_version":"1.0","source":{"id":"2111.11141","kind":"arxiv","version":2}},"canonical_sha256":"45caa0c7acbe4877624bca52bf8e9e98068e25cb35866675a891be97627235c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"45caa0c7acbe4877624bca52bf8e9e98068e25cb35866675a891be97627235c1","first_computed_at":"2026-07-05T05:27:16.582893Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:27:16.582893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V6T2ZPNdfQ3AXRXiZGqggnRq5c6rza8RhUyhpfHdEvYkYDOuEkJIcQK8ODvLDb2mupPAySt/q5bfW1w7gPg6Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:27:16.583350Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.11141","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e5c801520f4042b3242c9d82259b9e94c4a011d1aa625ea4ebcc53d759bd9d08","sha256:4924b0dfb424aab6e10434068273b0f73394e3dd1ae7b674fbe660761b2b6b34"],"state_sha256":"56a551ca26e8c205dbb8aa48105e6464b602bc17df6d036b3fb578370c03100f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w8Vmp7cGm4Wg5XaiJKsHxC1j655xBfrK9TC1fTLrOTdiL2clz8LpaXu+AZAD+n9WVnaM6P1J+mlbz8X4bWlQDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T15:59:30.640945Z","bundle_sha256":"fc9b745c6ce64f0a4a6fe7ec251fb26e58a44787a422f17689d38345d580c6ad"}}