{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:Q22COEW5IL3MXKZLIUOS6SMBHB","short_pith_number":"pith:Q22COEW5","canonical_record":{"source":{"id":"1812.11284","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-12-29T04:46:51Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"9c4ddbc0558fc3bcf888982f13b5e00552ba2eb93ea278c13a34260815d46514","abstract_canon_sha256":"14281063b12e5077a716520319c81c1774d601051559a5042e94b17f759fd6ff"},"schema_version":"1.0"},"canonical_sha256":"86b42712dd42f6cbab2b451d2f4981385897a3d4ff66456cd310faca3e0c0401","source":{"kind":"arxiv","id":"1812.11284","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.11284","created_at":"2026-05-17T23:57:12Z"},{"alias_kind":"arxiv_version","alias_value":"1812.11284v1","created_at":"2026-05-17T23:57:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.11284","created_at":"2026-05-17T23:57:12Z"},{"alias_kind":"pith_short_12","alias_value":"Q22COEW5IL3M","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_16","alias_value":"Q22COEW5IL3MXKZL","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_8","alias_value":"Q22COEW5","created_at":"2026-05-18T12:32:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:Q22COEW5IL3MXKZLIUOS6SMBHB","target":"record","payload":{"canonical_record":{"source":{"id":"1812.11284","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-12-29T04:46:51Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"9c4ddbc0558fc3bcf888982f13b5e00552ba2eb93ea278c13a34260815d46514","abstract_canon_sha256":"14281063b12e5077a716520319c81c1774d601051559a5042e94b17f759fd6ff"},"schema_version":"1.0"},"canonical_sha256":"86b42712dd42f6cbab2b451d2f4981385897a3d4ff66456cd310faca3e0c0401","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:57:12.336982Z","signature_b64":"tK7+UEJ7ZeVrw9dEbfObrsdHZIE9LXxG/m4RuIc4gUqiz3Xydn4jydkBwb8a/AopuymRFM6SeefyW5DZYH5vDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"86b42712dd42f6cbab2b451d2f4981385897a3d4ff66456cd310faca3e0c0401","last_reissued_at":"2026-05-17T23:57:12.336547Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:57:12.336547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.11284","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":"2026-05-17T23:57:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uCldxxevmUwGsud2u6QfTtKTf6eX6RSri01pALOQKxzYOWUzcvq7Jado+XWd5cq3wvNb6hZu3+2GxqcqmBqvCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T19:01:47.707986Z"},"content_sha256":"043a3605590c631672839646d8dbd112beb789791dd55478ab87269c5c6aa296","schema_version":"1.0","event_id":"sha256:043a3605590c631672839646d8dbd112beb789791dd55478ab87269c5c6aa296"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:Q22COEW5IL3MXKZLIUOS6SMBHB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"3D Convolution on RGB-D Point Clouds for Accurate Model-free Object Pose Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"cs.RO","authors_text":"Cunjun Yu, Quang-Cuong Pham, Zhongang Cai","submitted_at":"2018-12-29T04:46:51Z","abstract_excerpt":"The conventional pose estimation of a 3D object usually requires the knowledge of the 3D model of the object. Even with the recent development in convolutional neural networks (CNNs), a 3D model is often necessary in the final estimation. In this paper, we propose a two-stage pipeline that takes in raw colored point cloud data and estimates an object's translation and rotation by running 3D convolutions on voxels. The pipeline is simple yet highly accurate: translation error is reduced to the voxel resolution (around 1 cm) and rotation error is around 5 degrees. The pipeline is also put to act"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.11284","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":""},"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":"2026-05-17T23:57:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4K1EW2O0sXxu/m5wGa3k0YKN1HC2sXHQf1gHHiBz8q9oXtd67IpyH7hl9gV1YRN9gBgmsJW0ZvGbXkZ6XCf0Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T19:01:47.708345Z"},"content_sha256":"eaace400eca8b8c86eadb83cc6762fba1c13fc04b4c2799415841e35c2151d26","schema_version":"1.0","event_id":"sha256:eaace400eca8b8c86eadb83cc6762fba1c13fc04b4c2799415841e35c2151d26"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q22COEW5IL3MXKZLIUOS6SMBHB/bundle.json","state_url":"https://pith.science/pith/Q22COEW5IL3MXKZLIUOS6SMBHB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q22COEW5IL3MXKZLIUOS6SMBHB/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":"2026-06-01T19:01:47Z","links":{"resolver":"https://pith.science/pith/Q22COEW5IL3MXKZLIUOS6SMBHB","bundle":"https://pith.science/pith/Q22COEW5IL3MXKZLIUOS6SMBHB/bundle.json","state":"https://pith.science/pith/Q22COEW5IL3MXKZLIUOS6SMBHB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q22COEW5IL3MXKZLIUOS6SMBHB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:Q22COEW5IL3MXKZLIUOS6SMBHB","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":"14281063b12e5077a716520319c81c1774d601051559a5042e94b17f759fd6ff","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-12-29T04:46:51Z","title_canon_sha256":"9c4ddbc0558fc3bcf888982f13b5e00552ba2eb93ea278c13a34260815d46514"},"schema_version":"1.0","source":{"id":"1812.11284","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.11284","created_at":"2026-05-17T23:57:12Z"},{"alias_kind":"arxiv_version","alias_value":"1812.11284v1","created_at":"2026-05-17T23:57:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.11284","created_at":"2026-05-17T23:57:12Z"},{"alias_kind":"pith_short_12","alias_value":"Q22COEW5IL3M","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_16","alias_value":"Q22COEW5IL3MXKZL","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_8","alias_value":"Q22COEW5","created_at":"2026-05-18T12:32:46Z"}],"graph_snapshots":[{"event_id":"sha256:eaace400eca8b8c86eadb83cc6762fba1c13fc04b4c2799415841e35c2151d26","target":"graph","created_at":"2026-05-17T23:57:12Z","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"},"paper":{"abstract_excerpt":"The conventional pose estimation of a 3D object usually requires the knowledge of the 3D model of the object. Even with the recent development in convolutional neural networks (CNNs), a 3D model is often necessary in the final estimation. In this paper, we propose a two-stage pipeline that takes in raw colored point cloud data and estimates an object's translation and rotation by running 3D convolutions on voxels. The pipeline is simple yet highly accurate: translation error is reduced to the voxel resolution (around 1 cm) and rotation error is around 5 degrees. The pipeline is also put to act","authors_text":"Cunjun Yu, Quang-Cuong Pham, Zhongang Cai","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-12-29T04:46:51Z","title":"3D Convolution on RGB-D Point Clouds for Accurate Model-free Object Pose Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.11284","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":"sha256:043a3605590c631672839646d8dbd112beb789791dd55478ab87269c5c6aa296","target":"record","created_at":"2026-05-17T23:57:12Z","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":"14281063b12e5077a716520319c81c1774d601051559a5042e94b17f759fd6ff","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-12-29T04:46:51Z","title_canon_sha256":"9c4ddbc0558fc3bcf888982f13b5e00552ba2eb93ea278c13a34260815d46514"},"schema_version":"1.0","source":{"id":"1812.11284","kind":"arxiv","version":1}},"canonical_sha256":"86b42712dd42f6cbab2b451d2f4981385897a3d4ff66456cd310faca3e0c0401","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"86b42712dd42f6cbab2b451d2f4981385897a3d4ff66456cd310faca3e0c0401","first_computed_at":"2026-05-17T23:57:12.336547Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:12.336547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tK7+UEJ7ZeVrw9dEbfObrsdHZIE9LXxG/m4RuIc4gUqiz3Xydn4jydkBwb8a/AopuymRFM6SeefyW5DZYH5vDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:12.336982Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.11284","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:043a3605590c631672839646d8dbd112beb789791dd55478ab87269c5c6aa296","sha256:eaace400eca8b8c86eadb83cc6762fba1c13fc04b4c2799415841e35c2151d26"],"state_sha256":"2b0f0a82ae8a91723ce61e9c457deb7736424f816dd4dfb3c8bbeb27cb43ca0c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B1Tn46e5KCoItf21jSlJaFKHIR6KqhxbLCLJZsR40bDJtA+53YrPYaN68xo2/m0aajHXriLcN4a8rdplxR4hCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T19:01:47.710300Z","bundle_sha256":"7adb657891afaf490f9977f7fe4f01dad68eb6089943a8144083a4960b4a7927"}}