{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ESFYUFBO55JFTBMDCIDRDZ6WOF","short_pith_number":"pith:ESFYUFBO","canonical_record":{"source":{"id":"2408.02922","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-06T03:15:18Z","cross_cats_sorted":[],"title_canon_sha256":"ae16797cb5af2f3a7c67830dae4fa16a91dc358f4d9c2869401939159ce7c785","abstract_canon_sha256":"070efe7bc493a658013185bbb4c91eeb082d180f40410a9c9ac569d785ce3105"},"schema_version":"1.0"},"canonical_sha256":"248b8a142eef52598583120711e7d6714604c6d939ac28c5180b7e707dfd8099","source":{"kind":"arxiv","id":"2408.02922","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.02922","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"arxiv_version","alias_value":"2408.02922v3","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.02922","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"pith_short_12","alias_value":"ESFYUFBO55JF","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"pith_short_16","alias_value":"ESFYUFBO55JFTBMD","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"pith_short_8","alias_value":"ESFYUFBO","created_at":"2026-07-05T10:19:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ESFYUFBO55JFTBMDCIDRDZ6WOF","target":"record","payload":{"canonical_record":{"source":{"id":"2408.02922","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-06T03:15:18Z","cross_cats_sorted":[],"title_canon_sha256":"ae16797cb5af2f3a7c67830dae4fa16a91dc358f4d9c2869401939159ce7c785","abstract_canon_sha256":"070efe7bc493a658013185bbb4c91eeb082d180f40410a9c9ac569d785ce3105"},"schema_version":"1.0"},"canonical_sha256":"248b8a142eef52598583120711e7d6714604c6d939ac28c5180b7e707dfd8099","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:19:55.632615Z","signature_b64":"QR3WzvWQ3SLvB7FKaEfoHOpJxkhEuOr9o+Fmb6gAGIxhH0nVcFQeGjr+H7VredVp8tpJTxz8FsowrkTMcKWBDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"248b8a142eef52598583120711e7d6714604c6d939ac28c5180b7e707dfd8099","last_reissued_at":"2026-07-05T10:19:55.632142Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:19:55.632142Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.02922","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:19:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PeyCAr0xP+E2cJhKTY52NScfVkQZ92oQASq++UQoVEkrOUFF/6uhNEjWqsYE3zbMfCTzFPjZpmxfFhPK82lKCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T08:04:27.572953Z"},"content_sha256":"185274afd5667cb21491e735710fdc06f8a14f466763ce61782d09ca66c8766b","schema_version":"1.0","event_id":"sha256:185274afd5667cb21491e735710fdc06f8a14f466763ce61782d09ca66c8766b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ESFYUFBO55JFTBMDCIDRDZ6WOF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pose Magic: Efficient and Temporally Consistent Human Pose Estimation with a Hybrid Mamba-GCN Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Qingmin Liao, Qinpeng Cui, Qiqi Bao, Wenming Yang, Xinyi Zhang","submitted_at":"2024-08-06T03:15:18Z","abstract_excerpt":"Current state-of-the-art (SOTA) methods in 3D Human Pose Estimation (HPE) are primarily based on Transformers. However, existing Transformer-based 3D HPE backbones often encounter a trade-off between accuracy and computational efficiency. To resolve the above dilemma, in this work, we leverage recent advances in state space models and utilize Mamba for high-quality and efficient long-range modeling. Nonetheless, Mamba still faces challenges in precisely exploiting local dependencies between joints. To address these issues, we propose a new attention-free hybrid spatiotemporal architecture name"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.02922","kind":"arxiv","version":3},"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/2408.02922/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":"2026-07-05T10:19:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ClkqXqqujMYl7emsaR6GQ61bD6QZm7bFy1AE7eL7T6aOGTFhawXgGilreuZbOOViylorHcuS6OByPE9z8ribBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T08:04:27.573815Z"},"content_sha256":"a8019e74c7011cc6701479cd1ef6ca08fd7538f7b27dcb77d78ba9e327f6c2ed","schema_version":"1.0","event_id":"sha256:a8019e74c7011cc6701479cd1ef6ca08fd7538f7b27dcb77d78ba9e327f6c2ed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ESFYUFBO55JFTBMDCIDRDZ6WOF/bundle.json","state_url":"https://pith.science/pith/ESFYUFBO55JFTBMDCIDRDZ6WOF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ESFYUFBO55JFTBMDCIDRDZ6WOF/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":"2026-08-06T08:04:27Z","links":{"resolver":"https://pith.science/pith/ESFYUFBO55JFTBMDCIDRDZ6WOF","bundle":"https://pith.science/pith/ESFYUFBO55JFTBMDCIDRDZ6WOF/bundle.json","state":"https://pith.science/pith/ESFYUFBO55JFTBMDCIDRDZ6WOF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ESFYUFBO55JFTBMDCIDRDZ6WOF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ESFYUFBO55JFTBMDCIDRDZ6WOF","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":"070efe7bc493a658013185bbb4c91eeb082d180f40410a9c9ac569d785ce3105","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-06T03:15:18Z","title_canon_sha256":"ae16797cb5af2f3a7c67830dae4fa16a91dc358f4d9c2869401939159ce7c785"},"schema_version":"1.0","source":{"id":"2408.02922","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.02922","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"arxiv_version","alias_value":"2408.02922v3","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.02922","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"pith_short_12","alias_value":"ESFYUFBO55JF","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"pith_short_16","alias_value":"ESFYUFBO55JFTBMD","created_at":"2026-07-05T10:19:55Z"},{"alias_kind":"pith_short_8","alias_value":"ESFYUFBO","created_at":"2026-07-05T10:19:55Z"}],"graph_snapshots":[{"event_id":"sha256:a8019e74c7011cc6701479cd1ef6ca08fd7538f7b27dcb77d78ba9e327f6c2ed","target":"graph","created_at":"2026-07-05T10:19:55Z","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/2408.02922/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current state-of-the-art (SOTA) methods in 3D Human Pose Estimation (HPE) are primarily based on Transformers. However, existing Transformer-based 3D HPE backbones often encounter a trade-off between accuracy and computational efficiency. To resolve the above dilemma, in this work, we leverage recent advances in state space models and utilize Mamba for high-quality and efficient long-range modeling. Nonetheless, Mamba still faces challenges in precisely exploiting local dependencies between joints. To address these issues, we propose a new attention-free hybrid spatiotemporal architecture name","authors_text":"Qingmin Liao, Qinpeng Cui, Qiqi Bao, Wenming Yang, Xinyi Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-06T03:15:18Z","title":"Pose Magic: Efficient and Temporally Consistent Human Pose Estimation with a Hybrid Mamba-GCN Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.02922","kind":"arxiv","version":3},"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":"sha256:185274afd5667cb21491e735710fdc06f8a14f466763ce61782d09ca66c8766b","target":"record","created_at":"2026-07-05T10:19:55Z","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":"070efe7bc493a658013185bbb4c91eeb082d180f40410a9c9ac569d785ce3105","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-06T03:15:18Z","title_canon_sha256":"ae16797cb5af2f3a7c67830dae4fa16a91dc358f4d9c2869401939159ce7c785"},"schema_version":"1.0","source":{"id":"2408.02922","kind":"arxiv","version":3}},"canonical_sha256":"248b8a142eef52598583120711e7d6714604c6d939ac28c5180b7e707dfd8099","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"248b8a142eef52598583120711e7d6714604c6d939ac28c5180b7e707dfd8099","first_computed_at":"2026-07-05T10:19:55.632142Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:19:55.632142Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QR3WzvWQ3SLvB7FKaEfoHOpJxkhEuOr9o+Fmb6gAGIxhH0nVcFQeGjr+H7VredVp8tpJTxz8FsowrkTMcKWBDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:19:55.632615Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.02922","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:185274afd5667cb21491e735710fdc06f8a14f466763ce61782d09ca66c8766b","sha256:a8019e74c7011cc6701479cd1ef6ca08fd7538f7b27dcb77d78ba9e327f6c2ed"],"state_sha256":"a437cb3eea606e46e0709b68ec7e17febaa95ee7c7ae80906dec0b45d3dfcabe"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Kveh+qeW3KmecbWN6jPYaLj7aXh8t07ip0d5vNZXJJ1y/vi1dNMFe7/n+Us9DrhZw1xQzQDuLIFLQRy/s4xBDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T08:04:27.579810Z","bundle_sha256":"c1b85db0e42c80009283812218204be3758d2e1dbaf1ebfbf53e849e579a5b54"}}