{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:2ZPZR32PGMZZ7I5WQ2OES55OAR","short_pith_number":"pith:2ZPZR32P","canonical_record":{"source":{"id":"2507.06662","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-09T08:46:40Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"20fa7dd3cad2f27c0935e7f2b72aff0592d61aa396a5a6547bdd00fbf7878da0","abstract_canon_sha256":"c3cf65c9097c11ed6f56fc1202938c081358a211d2310ea24872ff82c0eab037"},"schema_version":"1.0"},"canonical_sha256":"d65f98ef4f33339fa3b6869c4977ae04796f974a7915a7d8af3a537d34fc8282","source":{"kind":"arxiv","id":"2507.06662","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.06662","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"arxiv_version","alias_value":"2507.06662v1","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.06662","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_12","alias_value":"2ZPZR32PGMZZ","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_16","alias_value":"2ZPZR32PGMZZ7I5W","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_8","alias_value":"2ZPZR32P","created_at":"2026-07-05T11:34:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:2ZPZR32PGMZZ7I5WQ2OES55OAR","target":"record","payload":{"canonical_record":{"source":{"id":"2507.06662","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-09T08:46:40Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"20fa7dd3cad2f27c0935e7f2b72aff0592d61aa396a5a6547bdd00fbf7878da0","abstract_canon_sha256":"c3cf65c9097c11ed6f56fc1202938c081358a211d2310ea24872ff82c0eab037"},"schema_version":"1.0"},"canonical_sha256":"d65f98ef4f33339fa3b6869c4977ae04796f974a7915a7d8af3a537d34fc8282","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:34:20.568642Z","signature_b64":"BP2aN/zexnfm5BZSGyRZAZLm+VVGJj+rJl4k7pw9aaS7BTfN2pdxZ7tS3hFwjpNxmSrgZmROGg7W3KfzZ5hhAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d65f98ef4f33339fa3b6869c4977ae04796f974a7915a7d8af3a537d34fc8282","last_reissued_at":"2026-07-05T11:34:20.568120Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:34:20.568120Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.06662","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:34:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l171IOGSyuQtR1clWddJJKsovwJtCiW+blKHIEs7hktJGm5jhdFoI4uDLB1ZELm6jp6k9yQnaYWdRCNcGhahDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T22:35:42.569999Z"},"content_sha256":"560df8983ff89884b1ed40c3f46603d9c269c01886824e212d84ceaf9d06124f","schema_version":"1.0","event_id":"sha256:560df8983ff89884b1ed40c3f46603d9c269c01886824e212d84ceaf9d06124f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:2ZPZR32PGMZZ7I5WQ2OES55OAR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MK-Pose: Category-Level Object Pose Estimation via Multimodal-Based Keypoint Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Dong Liu, Enfan Lan, Jingtai Liu, Peili Song, Yifan Yang","submitted_at":"2025-07-09T08:46:40Z","abstract_excerpt":"Category-level object pose estimation, which predicts the pose of objects within a known category without prior knowledge of individual instances, is essential in applications like warehouse automation and manufacturing. Existing methods relying on RGB images or point cloud data often struggle with object occlusion and generalization across different instances and categories. This paper proposes a multimodal-based keypoint learning framework (MK-Pose) that integrates RGB images, point clouds, and category-level textual descriptions. The model uses a self-supervised keypoint detection module en"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.06662","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/2507.06662/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":"2026-07-05T11:34:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CDDVQmmu4or4GrSi46sr2eaDei2RdHblbZfqL877HxpC3IOeEQOZFqS6kY9mckWWaBH5N8BYCM12dPgxEVEwBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T22:35:42.570541Z"},"content_sha256":"1af78c13ccf612ac05b50ea287aa26ac679661d3ce7dc10f24d6351631e5c34d","schema_version":"1.0","event_id":"sha256:1af78c13ccf612ac05b50ea287aa26ac679661d3ce7dc10f24d6351631e5c34d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2ZPZR32PGMZZ7I5WQ2OES55OAR/bundle.json","state_url":"https://pith.science/pith/2ZPZR32PGMZZ7I5WQ2OES55OAR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2ZPZR32PGMZZ7I5WQ2OES55OAR/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":"2026-08-12T22:35:42Z","links":{"resolver":"https://pith.science/pith/2ZPZR32PGMZZ7I5WQ2OES55OAR","bundle":"https://pith.science/pith/2ZPZR32PGMZZ7I5WQ2OES55OAR/bundle.json","state":"https://pith.science/pith/2ZPZR32PGMZZ7I5WQ2OES55OAR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2ZPZR32PGMZZ7I5WQ2OES55OAR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2ZPZR32PGMZZ7I5WQ2OES55OAR","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":"c3cf65c9097c11ed6f56fc1202938c081358a211d2310ea24872ff82c0eab037","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-09T08:46:40Z","title_canon_sha256":"20fa7dd3cad2f27c0935e7f2b72aff0592d61aa396a5a6547bdd00fbf7878da0"},"schema_version":"1.0","source":{"id":"2507.06662","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.06662","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"arxiv_version","alias_value":"2507.06662v1","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.06662","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_12","alias_value":"2ZPZR32PGMZZ","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_16","alias_value":"2ZPZR32PGMZZ7I5W","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_8","alias_value":"2ZPZR32P","created_at":"2026-07-05T11:34:20Z"}],"graph_snapshots":[{"event_id":"sha256:1af78c13ccf612ac05b50ea287aa26ac679661d3ce7dc10f24d6351631e5c34d","target":"graph","created_at":"2026-07-05T11:34:20Z","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/2507.06662/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Category-level object pose estimation, which predicts the pose of objects within a known category without prior knowledge of individual instances, is essential in applications like warehouse automation and manufacturing. Existing methods relying on RGB images or point cloud data often struggle with object occlusion and generalization across different instances and categories. This paper proposes a multimodal-based keypoint learning framework (MK-Pose) that integrates RGB images, point clouds, and category-level textual descriptions. The model uses a self-supervised keypoint detection module en","authors_text":"Dong Liu, Enfan Lan, Jingtai Liu, Peili Song, Yifan Yang","cross_cats":["cs.RO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-09T08:46:40Z","title":"MK-Pose: Category-Level Object Pose Estimation via Multimodal-Based Keypoint Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.06662","kind":"arxiv","version":1},"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":"sha256:560df8983ff89884b1ed40c3f46603d9c269c01886824e212d84ceaf9d06124f","target":"record","created_at":"2026-07-05T11:34:20Z","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":"c3cf65c9097c11ed6f56fc1202938c081358a211d2310ea24872ff82c0eab037","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-09T08:46:40Z","title_canon_sha256":"20fa7dd3cad2f27c0935e7f2b72aff0592d61aa396a5a6547bdd00fbf7878da0"},"schema_version":"1.0","source":{"id":"2507.06662","kind":"arxiv","version":1}},"canonical_sha256":"d65f98ef4f33339fa3b6869c4977ae04796f974a7915a7d8af3a537d34fc8282","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d65f98ef4f33339fa3b6869c4977ae04796f974a7915a7d8af3a537d34fc8282","first_computed_at":"2026-07-05T11:34:20.568120Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:34:20.568120Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BP2aN/zexnfm5BZSGyRZAZLm+VVGJj+rJl4k7pw9aaS7BTfN2pdxZ7tS3hFwjpNxmSrgZmROGg7W3KfzZ5hhAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:34:20.568642Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.06662","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:560df8983ff89884b1ed40c3f46603d9c269c01886824e212d84ceaf9d06124f","sha256:1af78c13ccf612ac05b50ea287aa26ac679661d3ce7dc10f24d6351631e5c34d"],"state_sha256":"9f570ed65764844073ca906e641c8baafaa63995191b1ba3fbbcbffba39a5eeb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f2lAh9KYQ6DNxrBEv0lGiWotpoqqjYU4v55tULAv71kzdvwNwFrpYbw4QjC6OkEhh2NTsoWWYkaFHbuaBF1dCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T22:35:42.580095Z","bundle_sha256":"17e397d0583936d5cc4d6cc80ce183260407195fa5450e230b7fdaad65cd8146"}}