{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:6YMBOUBAMXREC763RZNK2JT4Z2","short_pith_number":"pith:6YMBOUBA","canonical_record":{"source":{"id":"1812.00333","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-02T05:38:59Z","cross_cats_sorted":[],"title_canon_sha256":"50cc76692d30ae552b7c09df5dddcbd1855832379150cdb71c8bef1c5c0ab58c","abstract_canon_sha256":"4329120a3baece9acc4b462f411262ede789eb6aa80d1aa3ad0898e672a5960b"},"schema_version":"1.0"},"canonical_sha256":"f61817502065e2417fdb8e5aad267cce84b85564402ad5f54e9ffbf3018c057e","source":{"kind":"arxiv","id":"1812.00333","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.00333","created_at":"2026-05-17T23:59:21Z"},{"alias_kind":"arxiv_version","alias_value":"1812.00333v1","created_at":"2026-05-17T23:59:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.00333","created_at":"2026-05-17T23:59:21Z"},{"alias_kind":"pith_short_12","alias_value":"6YMBOUBAMXRE","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"6YMBOUBAMXREC763","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"6YMBOUBA","created_at":"2026-05-18T12:32:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:6YMBOUBAMXREC763RZNK2JT4Z2","target":"record","payload":{"canonical_record":{"source":{"id":"1812.00333","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-02T05:38:59Z","cross_cats_sorted":[],"title_canon_sha256":"50cc76692d30ae552b7c09df5dddcbd1855832379150cdb71c8bef1c5c0ab58c","abstract_canon_sha256":"4329120a3baece9acc4b462f411262ede789eb6aa80d1aa3ad0898e672a5960b"},"schema_version":"1.0"},"canonical_sha256":"f61817502065e2417fdb8e5aad267cce84b85564402ad5f54e9ffbf3018c057e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:21.587520Z","signature_b64":"IINoeNhq49ZDkSv63Leay0y6lNXo3yp2Qp5qSICUk8GTkmGcKZMG7Ueh3LxLy1TnxjoIZYbcGUmVgXxvN0HeDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f61817502065e2417fdb8e5aad267cce84b85564402ad5f54e9ffbf3018c057e","last_reissued_at":"2026-05-17T23:59:21.587050Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:21.587050Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.00333","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":"2026-05-17T23:59:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P9dNVEuwnb0y+8rThdOK1/jJvGff+UdUD/yeKdwyHFkjMQxa+wJ2TWum0qZzJlfU7fSjjtDqNzQ8XF+B+b/HCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T15:45:44.302475Z"},"content_sha256":"17328716e0e5f2dcc1cd3b3075577d5562e138176039726300c247b58561d882","schema_version":"1.0","event_id":"sha256:17328716e0e5f2dcc1cd3b3075577d5562e138176039726300c247b58561d882"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:6YMBOUBAMXREC763RZNK2JT4Z2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PVRNet: Point-View Relation Neural Network for 3D Shape Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Changqing Zou, Haoxuan You, Rongrong Ji, Xibin Zhao, Yifan Feng, Yue Gao","submitted_at":"2018-12-02T05:38:59Z","abstract_excerpt":"Three-dimensional (3D) shape recognition has drawn much research attention in the field of computer vision. The advances of deep learning encourage various deep models for 3D feature representation. For point cloud and multi-view data, two popular 3D data modalities, different models are proposed with remarkable performance. However the relation between point cloud and views has been rarely investigated. In this paper, we introduce Point-View Relation Network (PVRNet), an effective network designed to well fuse the view features and the point cloud feature with a proposed relation score module"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.00333","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":"2026-05-17T23:59:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UOXg0pWup4aZ7CFIksqfcfmVYa59LA1my23bM+VAvEYwWoLS0o+P1wrJrUAoREFCQ7qFeGKYQH34uFcgtrGoAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T15:45:44.302850Z"},"content_sha256":"b12d144c2a2fd68e0dbc06dc7f4309d6d39c84affe591cdd22555324c43180f7","schema_version":"1.0","event_id":"sha256:b12d144c2a2fd68e0dbc06dc7f4309d6d39c84affe591cdd22555324c43180f7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6YMBOUBAMXREC763RZNK2JT4Z2/bundle.json","state_url":"https://pith.science/pith/6YMBOUBAMXREC763RZNK2JT4Z2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6YMBOUBAMXREC763RZNK2JT4Z2/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":"2026-05-20T15:45:44Z","links":{"resolver":"https://pith.science/pith/6YMBOUBAMXREC763RZNK2JT4Z2","bundle":"https://pith.science/pith/6YMBOUBAMXREC763RZNK2JT4Z2/bundle.json","state":"https://pith.science/pith/6YMBOUBAMXREC763RZNK2JT4Z2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6YMBOUBAMXREC763RZNK2JT4Z2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:6YMBOUBAMXREC763RZNK2JT4Z2","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":"4329120a3baece9acc4b462f411262ede789eb6aa80d1aa3ad0898e672a5960b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-02T05:38:59Z","title_canon_sha256":"50cc76692d30ae552b7c09df5dddcbd1855832379150cdb71c8bef1c5c0ab58c"},"schema_version":"1.0","source":{"id":"1812.00333","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.00333","created_at":"2026-05-17T23:59:21Z"},{"alias_kind":"arxiv_version","alias_value":"1812.00333v1","created_at":"2026-05-17T23:59:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.00333","created_at":"2026-05-17T23:59:21Z"},{"alias_kind":"pith_short_12","alias_value":"6YMBOUBAMXRE","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"6YMBOUBAMXREC763","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"6YMBOUBA","created_at":"2026-05-18T12:32:11Z"}],"graph_snapshots":[{"event_id":"sha256:b12d144c2a2fd68e0dbc06dc7f4309d6d39c84affe591cdd22555324c43180f7","target":"graph","created_at":"2026-05-17T23:59:21Z","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":"Three-dimensional (3D) shape recognition has drawn much research attention in the field of computer vision. The advances of deep learning encourage various deep models for 3D feature representation. For point cloud and multi-view data, two popular 3D data modalities, different models are proposed with remarkable performance. However the relation between point cloud and views has been rarely investigated. In this paper, we introduce Point-View Relation Network (PVRNet), an effective network designed to well fuse the view features and the point cloud feature with a proposed relation score module","authors_text":"Changqing Zou, Haoxuan You, Rongrong Ji, Xibin Zhao, Yifan Feng, Yue Gao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-02T05:38:59Z","title":"PVRNet: Point-View Relation Neural Network for 3D Shape Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.00333","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":"sha256:17328716e0e5f2dcc1cd3b3075577d5562e138176039726300c247b58561d882","target":"record","created_at":"2026-05-17T23:59:21Z","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":"4329120a3baece9acc4b462f411262ede789eb6aa80d1aa3ad0898e672a5960b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-02T05:38:59Z","title_canon_sha256":"50cc76692d30ae552b7c09df5dddcbd1855832379150cdb71c8bef1c5c0ab58c"},"schema_version":"1.0","source":{"id":"1812.00333","kind":"arxiv","version":1}},"canonical_sha256":"f61817502065e2417fdb8e5aad267cce84b85564402ad5f54e9ffbf3018c057e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f61817502065e2417fdb8e5aad267cce84b85564402ad5f54e9ffbf3018c057e","first_computed_at":"2026-05-17T23:59:21.587050Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:59:21.587050Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IINoeNhq49ZDkSv63Leay0y6lNXo3yp2Qp5qSICUk8GTkmGcKZMG7Ueh3LxLy1TnxjoIZYbcGUmVgXxvN0HeDg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:59:21.587520Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.00333","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:17328716e0e5f2dcc1cd3b3075577d5562e138176039726300c247b58561d882","sha256:b12d144c2a2fd68e0dbc06dc7f4309d6d39c84affe591cdd22555324c43180f7"],"state_sha256":"48f71b52cd652a5a7e412be92b689db4b162e35d068e227aefa2c9fd0e35280d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aLZowMwgIyFoOQxQXk3qH3aRJotlL4n6kgMpzKWSUoN80cC5GWtxbhBkQ2CsMQlqLSD01wUguKvmjEH7YK4iDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-20T15:45:44.304967Z","bundle_sha256":"3f00cc0280b105393de8afcef01a2102a43ccbd3d5a46429446526418bb2c933"}}