{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:ERNJHP4FN557XYNOMGDLONKADC","short_pith_number":"pith:ERNJHP4F","canonical_record":{"source":{"id":"2601.16763","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-01-23T14:09:33Z","cross_cats_sorted":[],"title_canon_sha256":"827acab82f3924e489aae80989693800b46acf9c235612b23ec154b7013d9a75","abstract_canon_sha256":"90466441e75b1d15fbfc3a25c8b79a5254bbe80fe594ce14a759f1611b1d3c4a"},"schema_version":"1.0"},"canonical_sha256":"245a93bf856f7bfbe1ae6186b735401882bef8ec80cb5b8287c9addafc6e9ab1","source":{"kind":"arxiv","id":"2601.16763","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.16763","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"arxiv_version","alias_value":"2601.16763v2","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.16763","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"pith_short_12","alias_value":"ERNJHP4FN557","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"pith_short_16","alias_value":"ERNJHP4FN557XYNO","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"pith_short_8","alias_value":"ERNJHP4F","created_at":"2026-05-26T01:03:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:ERNJHP4FN557XYNOMGDLONKADC","target":"record","payload":{"canonical_record":{"source":{"id":"2601.16763","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-01-23T14:09:33Z","cross_cats_sorted":[],"title_canon_sha256":"827acab82f3924e489aae80989693800b46acf9c235612b23ec154b7013d9a75","abstract_canon_sha256":"90466441e75b1d15fbfc3a25c8b79a5254bbe80fe594ce14a759f1611b1d3c4a"},"schema_version":"1.0"},"canonical_sha256":"245a93bf856f7bfbe1ae6186b735401882bef8ec80cb5b8287c9addafc6e9ab1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T01:03:23.011424Z","signature_b64":"AIP+of6474G6PZqBl19QjWwOaQt+ArWfx6EeeEqNlzhOfuzVaH1FeD3Ay67eH2vYIp3BWBPquTJqwRleVD3ADw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"245a93bf856f7bfbe1ae6186b735401882bef8ec80cb5b8287c9addafc6e9ab1","last_reissued_at":"2026-05-26T01:03:23.010440Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T01:03:23.010440Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2601.16763","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":"2026-05-26T01:03:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DZ/rq6FlzEBquADYgREiw0GwyHNjwwUPtOfJdBMIEdt6IEX1ocRZT1WiiNYPlz9NXuS/jdqgItFCSVbyjp9WAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T17:02:39.676774Z"},"content_sha256":"c86a70bd722948459aedd2b1001a5c1324841efc768a55b09be0a27fce1877cd","schema_version":"1.0","event_id":"sha256:c86a70bd722948459aedd2b1001a5c1324841efc768a55b09be0a27fce1877cd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:ERNJHP4FN557XYNOMGDLONKADC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Flow Matching for Probabilistic Monocular 3D Human Pose Estimation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bastian Wandt, Cuong Le, M{\\aa}rten Wadenb\\\"ack, Pavlo Melnyk","submitted_at":"2026-01-23T14:09:33Z","abstract_excerpt":"Recovering 3D human poses from a monocular camera view is a highly ill-posed problem due to the depth ambiguity. Earlier studies on 3D human pose lifting from 2D often contain incorrect-yet-overconfident 3D estimations. To mitigate the problem, emerging probabilistic approaches treat the 3D estimations as a distribution, taking into account the uncertainty measurement of the poses. Falling in a similar category, we proposed FMPose, a probabilistic 3D human pose estimation method based on the flow matching generative approach. Conditioned on the 2D cues, the flow matching scheme learns the opti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.16763","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/2601.16763/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":"2026-05-26T01:03:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LmotozkP3IE1c5JGqVoDq1YUuDscBYWiaBuRsZw+ZI8ff+b/e6ErGAySzRTEF6WsBWdALGz+m7BEItldB0nzDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T17:02:39.677153Z"},"content_sha256":"2a6c29085c56f5372e455eb179db0044186f0d12dd11ed8794d3347d79225d36","schema_version":"1.0","event_id":"sha256:2a6c29085c56f5372e455eb179db0044186f0d12dd11ed8794d3347d79225d36"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ERNJHP4FN557XYNOMGDLONKADC/bundle.json","state_url":"https://pith.science/pith/ERNJHP4FN557XYNOMGDLONKADC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ERNJHP4FN557XYNOMGDLONKADC/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":"2026-06-04T17:02:39Z","links":{"resolver":"https://pith.science/pith/ERNJHP4FN557XYNOMGDLONKADC","bundle":"https://pith.science/pith/ERNJHP4FN557XYNOMGDLONKADC/bundle.json","state":"https://pith.science/pith/ERNJHP4FN557XYNOMGDLONKADC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ERNJHP4FN557XYNOMGDLONKADC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ERNJHP4FN557XYNOMGDLONKADC","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":"90466441e75b1d15fbfc3a25c8b79a5254bbe80fe594ce14a759f1611b1d3c4a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-01-23T14:09:33Z","title_canon_sha256":"827acab82f3924e489aae80989693800b46acf9c235612b23ec154b7013d9a75"},"schema_version":"1.0","source":{"id":"2601.16763","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.16763","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"arxiv_version","alias_value":"2601.16763v2","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.16763","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"pith_short_12","alias_value":"ERNJHP4FN557","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"pith_short_16","alias_value":"ERNJHP4FN557XYNO","created_at":"2026-05-26T01:03:23Z"},{"alias_kind":"pith_short_8","alias_value":"ERNJHP4F","created_at":"2026-05-26T01:03:23Z"}],"graph_snapshots":[{"event_id":"sha256:2a6c29085c56f5372e455eb179db0044186f0d12dd11ed8794d3347d79225d36","target":"graph","created_at":"2026-05-26T01:03:23Z","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/2601.16763/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recovering 3D human poses from a monocular camera view is a highly ill-posed problem due to the depth ambiguity. Earlier studies on 3D human pose lifting from 2D often contain incorrect-yet-overconfident 3D estimations. To mitigate the problem, emerging probabilistic approaches treat the 3D estimations as a distribution, taking into account the uncertainty measurement of the poses. Falling in a similar category, we proposed FMPose, a probabilistic 3D human pose estimation method based on the flow matching generative approach. Conditioned on the 2D cues, the flow matching scheme learns the opti","authors_text":"Bastian Wandt, Cuong Le, M{\\aa}rten Wadenb\\\"ack, Pavlo Melnyk","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-01-23T14:09:33Z","title":"Flow Matching for Probabilistic Monocular 3D Human Pose Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.16763","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:c86a70bd722948459aedd2b1001a5c1324841efc768a55b09be0a27fce1877cd","target":"record","created_at":"2026-05-26T01:03:23Z","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":"90466441e75b1d15fbfc3a25c8b79a5254bbe80fe594ce14a759f1611b1d3c4a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-01-23T14:09:33Z","title_canon_sha256":"827acab82f3924e489aae80989693800b46acf9c235612b23ec154b7013d9a75"},"schema_version":"1.0","source":{"id":"2601.16763","kind":"arxiv","version":2}},"canonical_sha256":"245a93bf856f7bfbe1ae6186b735401882bef8ec80cb5b8287c9addafc6e9ab1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"245a93bf856f7bfbe1ae6186b735401882bef8ec80cb5b8287c9addafc6e9ab1","first_computed_at":"2026-05-26T01:03:23.010440Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T01:03:23.010440Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AIP+of6474G6PZqBl19QjWwOaQt+ArWfx6EeeEqNlzhOfuzVaH1FeD3Ay67eH2vYIp3BWBPquTJqwRleVD3ADw==","signature_status":"signed_v1","signed_at":"2026-05-26T01:03:23.011424Z","signed_message":"canonical_sha256_bytes"},"source_id":"2601.16763","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c86a70bd722948459aedd2b1001a5c1324841efc768a55b09be0a27fce1877cd","sha256:2a6c29085c56f5372e455eb179db0044186f0d12dd11ed8794d3347d79225d36"],"state_sha256":"46c4fd65c3eee50b2ac9778177737cf3da3f90bd9f5793f033e31052906f2c33"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6HpYUmso0wszDwwHfRhNk9yKH9XYg8Rit6VEJvc4swguOyLoKtrkpIc9fFRNvPUz4W7uxpVOQG/Ig1UhXIKyCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T17:02:39.679267Z","bundle_sha256":"c849a589f6954a50e9d8c2dc5ed6bbec304973a35375844b5960b00d24a59c98"}}