{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:TVA75XX62P53EBS24JR22VBVJ5","short_pith_number":"pith:TVA75XX6","canonical_record":{"source":{"id":"2206.08497","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.GR","submitted_at":"2022-06-17T00:50:36Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"c8f37c744326ed386fb5a93466bf9d2d86be389bfeb57dc0ea05b37fba6fe5dc","abstract_canon_sha256":"6eadc846c98527ba92ed150278400596f66fcdb948c8590041f44084448871ee"},"schema_version":"1.0"},"canonical_sha256":"9d41fedefed3fbb2065ae263ad54354f6b03d1bd0a9b10116b60d3c0905afa4a","source":{"kind":"arxiv","id":"2206.08497","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.08497","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"arxiv_version","alias_value":"2206.08497v1","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.08497","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"pith_short_12","alias_value":"TVA75XX62P53","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"pith_short_16","alias_value":"TVA75XX62P53EBS2","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"pith_short_8","alias_value":"TVA75XX6","created_at":"2026-07-05T04:32:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:TVA75XX62P53EBS24JR22VBVJ5","target":"record","payload":{"canonical_record":{"source":{"id":"2206.08497","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.GR","submitted_at":"2022-06-17T00:50:36Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"c8f37c744326ed386fb5a93466bf9d2d86be389bfeb57dc0ea05b37fba6fe5dc","abstract_canon_sha256":"6eadc846c98527ba92ed150278400596f66fcdb948c8590041f44084448871ee"},"schema_version":"1.0"},"canonical_sha256":"9d41fedefed3fbb2065ae263ad54354f6b03d1bd0a9b10116b60d3c0905afa4a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:32:30.318609Z","signature_b64":"n9Pu5/OcS65nxqCoy9IJME15VdzJOYXF4mwAtD48d/ml5Fri+vNaZreJzIbrVnkCoX6H0cFetshtjt1wqGFRCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9d41fedefed3fbb2065ae263ad54354f6b03d1bd0a9b10116b60d3c0905afa4a","last_reissued_at":"2026-07-05T04:32:30.318100Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:32:30.318100Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2206.08497","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":"2026-07-05T04:32:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QOt1ifwp7rk/dpbKgITN3WKIH7j2aVvK6l8hIWxFFyPpRZP5GxCf/Myi2O3A7IlwfwAH+MUXLAtMqCr1XVA2Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T05:15:13.508572Z"},"content_sha256":"254bd8153603d53abdf545c41227640d524fe87b5262d7e857e91c0c1000a875","schema_version":"1.0","event_id":"sha256:254bd8153603d53abdf545c41227640d524fe87b5262d7e857e91c0c1000a875"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:TVA75XX62P53EBS24JR22VBVJ5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Kinematic Motion Detection for Part-segmented 3D Shape Collections","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.GR","authors_text":"Daniel Ritchie, Srinath Sridhar, Xianghao Xu, Yifan Ruan","submitted_at":"2022-06-17T00:50:36Z","abstract_excerpt":"3D models of manufactured objects are important for populating virtual worlds and for synthetic data generation for vision and robotics. To be most useful, such objects should be articulated: their parts should move when interacted with. While articulated object datasets exist, creating them is labor-intensive. Learning-based prediction of part motions can help, but all existing methods require annotated training data. In this paper, we present an unsupervised approach for discovering articulated motions in a part-segmented 3D shape collection. Our approach is based on a concept we call catego"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.08497","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/2206.08497/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":"2026-07-05T04:32:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oVw3TMY7/HgLzAiJrrkENMLQlGe/FIVDzrJ4ZMsKzOeKtWmh4puecKadbP7kXUlCU7PcYm1oxsae7fBuZVa4AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T05:15:13.509068Z"},"content_sha256":"45b7bb853ab1d779c672fd403d69eb5661f9fba1779f6a5697334a4334dd1d63","schema_version":"1.0","event_id":"sha256:45b7bb853ab1d779c672fd403d69eb5661f9fba1779f6a5697334a4334dd1d63"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TVA75XX62P53EBS24JR22VBVJ5/bundle.json","state_url":"https://pith.science/pith/TVA75XX62P53EBS24JR22VBVJ5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TVA75XX62P53EBS24JR22VBVJ5/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":"2026-08-07T05:15:13Z","links":{"resolver":"https://pith.science/pith/TVA75XX62P53EBS24JR22VBVJ5","bundle":"https://pith.science/pith/TVA75XX62P53EBS24JR22VBVJ5/bundle.json","state":"https://pith.science/pith/TVA75XX62P53EBS24JR22VBVJ5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TVA75XX62P53EBS24JR22VBVJ5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:TVA75XX62P53EBS24JR22VBVJ5","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":"6eadc846c98527ba92ed150278400596f66fcdb948c8590041f44084448871ee","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.GR","submitted_at":"2022-06-17T00:50:36Z","title_canon_sha256":"c8f37c744326ed386fb5a93466bf9d2d86be389bfeb57dc0ea05b37fba6fe5dc"},"schema_version":"1.0","source":{"id":"2206.08497","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.08497","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"arxiv_version","alias_value":"2206.08497v1","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.08497","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"pith_short_12","alias_value":"TVA75XX62P53","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"pith_short_16","alias_value":"TVA75XX62P53EBS2","created_at":"2026-07-05T04:32:30Z"},{"alias_kind":"pith_short_8","alias_value":"TVA75XX6","created_at":"2026-07-05T04:32:30Z"}],"graph_snapshots":[{"event_id":"sha256:45b7bb853ab1d779c672fd403d69eb5661f9fba1779f6a5697334a4334dd1d63","target":"graph","created_at":"2026-07-05T04:32:30Z","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/2206.08497/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"3D models of manufactured objects are important for populating virtual worlds and for synthetic data generation for vision and robotics. To be most useful, such objects should be articulated: their parts should move when interacted with. While articulated object datasets exist, creating them is labor-intensive. Learning-based prediction of part motions can help, but all existing methods require annotated training data. In this paper, we present an unsupervised approach for discovering articulated motions in a part-segmented 3D shape collection. Our approach is based on a concept we call catego","authors_text":"Daniel Ritchie, Srinath Sridhar, Xianghao Xu, Yifan Ruan","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.GR","submitted_at":"2022-06-17T00:50:36Z","title":"Unsupervised Kinematic Motion Detection for Part-segmented 3D Shape Collections"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.08497","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":"sha256:254bd8153603d53abdf545c41227640d524fe87b5262d7e857e91c0c1000a875","target":"record","created_at":"2026-07-05T04:32:30Z","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":"6eadc846c98527ba92ed150278400596f66fcdb948c8590041f44084448871ee","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.GR","submitted_at":"2022-06-17T00:50:36Z","title_canon_sha256":"c8f37c744326ed386fb5a93466bf9d2d86be389bfeb57dc0ea05b37fba6fe5dc"},"schema_version":"1.0","source":{"id":"2206.08497","kind":"arxiv","version":1}},"canonical_sha256":"9d41fedefed3fbb2065ae263ad54354f6b03d1bd0a9b10116b60d3c0905afa4a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9d41fedefed3fbb2065ae263ad54354f6b03d1bd0a9b10116b60d3c0905afa4a","first_computed_at":"2026-07-05T04:32:30.318100Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:32:30.318100Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"n9Pu5/OcS65nxqCoy9IJME15VdzJOYXF4mwAtD48d/ml5Fri+vNaZreJzIbrVnkCoX6H0cFetshtjt1wqGFRCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:32:30.318609Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.08497","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:254bd8153603d53abdf545c41227640d524fe87b5262d7e857e91c0c1000a875","sha256:45b7bb853ab1d779c672fd403d69eb5661f9fba1779f6a5697334a4334dd1d63"],"state_sha256":"2303add08f56037a0e13e6a38ec5b8b30c3794fb4d3922c4a8ad5ee469791a87"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8yLOjQCZp6Jocbvq1PCD9sSykiQgkbQbh1grcApmeIBMBnjivamM6rP3JRKGoEdj9Y3cX44RlgVL9vsLedCiDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T05:15:13.514091Z","bundle_sha256":"7f9c4afeb625e04fd715b2e8660276cae3f456940561f2495c0c3a94f20a89f4"}}