{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:7G3IFWITZOB5SFL4323WC75GCG","short_pith_number":"pith:7G3IFWIT","canonical_record":{"source":{"id":"1907.03670","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-08T15:19:48Z","cross_cats_sorted":[],"title_canon_sha256":"bc5840fa61d57b910c7c79ce75445b1c5d1dd2106eb1a8559521e73ac883ea81","abstract_canon_sha256":"e958c87b23f810715ac595cbcfc4e14761a60b6a9ccc0d1cded50ae4525c6b15"},"schema_version":"1.0"},"canonical_sha256":"f9b682d913cb83d9157cdeb7617fa6118ffc04e8e78f4e005b0c66e008f0dc92","source":{"kind":"arxiv","id":"1907.03670","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.03670","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"arxiv_version","alias_value":"1907.03670v3","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.03670","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"pith_short_12","alias_value":"7G3IFWITZOB5","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"pith_short_16","alias_value":"7G3IFWITZOB5SFL4","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"pith_short_8","alias_value":"7G3IFWIT","created_at":"2026-07-05T00:47:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:7G3IFWITZOB5SFL4323WC75GCG","target":"record","payload":{"canonical_record":{"source":{"id":"1907.03670","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-08T15:19:48Z","cross_cats_sorted":[],"title_canon_sha256":"bc5840fa61d57b910c7c79ce75445b1c5d1dd2106eb1a8559521e73ac883ea81","abstract_canon_sha256":"e958c87b23f810715ac595cbcfc4e14761a60b6a9ccc0d1cded50ae4525c6b15"},"schema_version":"1.0"},"canonical_sha256":"f9b682d913cb83d9157cdeb7617fa6118ffc04e8e78f4e005b0c66e008f0dc92","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:47:58.184224Z","signature_b64":"3yMskku3LNMV9N0N1hl8v1fQlkB7y6Z/WpFIepfbS8w4yFVToaDjEJW2u+UhHJ4pJ0HAiyKeT05bgxKkwidABw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f9b682d913cb83d9157cdeb7617fa6118ffc04e8e78f4e005b0c66e008f0dc92","last_reissued_at":"2026-07-05T00:47:58.183772Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:47:58.183772Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.03670","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":"2026-07-05T00:47:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"epnW3JLruTgG+GyVupEDFyR/IiUZrADo54gCu27vS2TbJ1Yg4R+Xi7sSYZEwzK6V16SailA8j7tFmLBZzFVlBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:04:58.630745Z"},"content_sha256":"3dacd7ba29daaa9cd3bfdd447fe3c9548769157cd3c4f2924c8c93522381e065","schema_version":"1.0","event_id":"sha256:3dacd7ba29daaa9cd3bfdd447fe3c9548769157cd3c4f2924c8c93522381e065"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:7G3IFWITZOB5SFL4323WC75GCG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hongsheng Li, Jianping Shi, Shaoshuai Shi, Xiaogang Wang, Zhe Wang","submitted_at":"2019-07-08T15:19:48Z","abstract_excerpt":"3D object detection from LiDAR point cloud is a challenging problem in 3D scene understanding and has many practical applications. In this paper, we extend our preliminary work PointRCNN to a novel and strong point-cloud-based 3D object detection framework, the part-aware and aggregation neural network (Part-$A^2$ net). The whole framework consists of the part-aware stage and the part-aggregation stage. Firstly, the part-aware stage for the first time fully utilizes free-of-charge part supervisions derived from 3D ground-truth boxes to simultaneously predict high quality 3D proposals and accur"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.03670","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/1907.03670/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":"2026-07-05T00:47:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yyVYdIypxYmA1d7ISO+uC7j76IwLE/rlRVdvzW05cWreGGV6vXZho7UOkrZLAiZxafqTfdQXhUFcQi+cqRFsDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:04:58.631704Z"},"content_sha256":"5d662e39379b5ae1a499f8d8f3dbf4cebe4d91089044c3bdb01a333b5f079207","schema_version":"1.0","event_id":"sha256:5d662e39379b5ae1a499f8d8f3dbf4cebe4d91089044c3bdb01a333b5f079207"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7G3IFWITZOB5SFL4323WC75GCG/bundle.json","state_url":"https://pith.science/pith/7G3IFWITZOB5SFL4323WC75GCG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7G3IFWITZOB5SFL4323WC75GCG/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":"2026-08-07T21:04:58Z","links":{"resolver":"https://pith.science/pith/7G3IFWITZOB5SFL4323WC75GCG","bundle":"https://pith.science/pith/7G3IFWITZOB5SFL4323WC75GCG/bundle.json","state":"https://pith.science/pith/7G3IFWITZOB5SFL4323WC75GCG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7G3IFWITZOB5SFL4323WC75GCG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:7G3IFWITZOB5SFL4323WC75GCG","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":"e958c87b23f810715ac595cbcfc4e14761a60b6a9ccc0d1cded50ae4525c6b15","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-08T15:19:48Z","title_canon_sha256":"bc5840fa61d57b910c7c79ce75445b1c5d1dd2106eb1a8559521e73ac883ea81"},"schema_version":"1.0","source":{"id":"1907.03670","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.03670","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"arxiv_version","alias_value":"1907.03670v3","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.03670","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"pith_short_12","alias_value":"7G3IFWITZOB5","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"pith_short_16","alias_value":"7G3IFWITZOB5SFL4","created_at":"2026-07-05T00:47:58Z"},{"alias_kind":"pith_short_8","alias_value":"7G3IFWIT","created_at":"2026-07-05T00:47:58Z"}],"graph_snapshots":[{"event_id":"sha256:5d662e39379b5ae1a499f8d8f3dbf4cebe4d91089044c3bdb01a333b5f079207","target":"graph","created_at":"2026-07-05T00:47:58Z","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/1907.03670/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"3D object detection from LiDAR point cloud is a challenging problem in 3D scene understanding and has many practical applications. In this paper, we extend our preliminary work PointRCNN to a novel and strong point-cloud-based 3D object detection framework, the part-aware and aggregation neural network (Part-$A^2$ net). The whole framework consists of the part-aware stage and the part-aggregation stage. Firstly, the part-aware stage for the first time fully utilizes free-of-charge part supervisions derived from 3D ground-truth boxes to simultaneously predict high quality 3D proposals and accur","authors_text":"Hongsheng Li, Jianping Shi, Shaoshuai Shi, Xiaogang Wang, Zhe Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-08T15:19:48Z","title":"From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.03670","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":"sha256:3dacd7ba29daaa9cd3bfdd447fe3c9548769157cd3c4f2924c8c93522381e065","target":"record","created_at":"2026-07-05T00:47:58Z","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":"e958c87b23f810715ac595cbcfc4e14761a60b6a9ccc0d1cded50ae4525c6b15","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-08T15:19:48Z","title_canon_sha256":"bc5840fa61d57b910c7c79ce75445b1c5d1dd2106eb1a8559521e73ac883ea81"},"schema_version":"1.0","source":{"id":"1907.03670","kind":"arxiv","version":3}},"canonical_sha256":"f9b682d913cb83d9157cdeb7617fa6118ffc04e8e78f4e005b0c66e008f0dc92","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f9b682d913cb83d9157cdeb7617fa6118ffc04e8e78f4e005b0c66e008f0dc92","first_computed_at":"2026-07-05T00:47:58.183772Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:47:58.183772Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3yMskku3LNMV9N0N1hl8v1fQlkB7y6Z/WpFIepfbS8w4yFVToaDjEJW2u+UhHJ4pJ0HAiyKeT05bgxKkwidABw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:47:58.184224Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.03670","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3dacd7ba29daaa9cd3bfdd447fe3c9548769157cd3c4f2924c8c93522381e065","sha256:5d662e39379b5ae1a499f8d8f3dbf4cebe4d91089044c3bdb01a333b5f079207"],"state_sha256":"c2f31a444c32c882be62fcd6fba63704663c9bfa39dbcb2216ee711032818a10"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PJ42cAzaG1rBDmitHqn8uufMM3I3gDxxDvCOA9/ijOJ3fU+DTXZulni6glJNoJ+qsFH208/PiKRkNz+M/WisDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T21:04:58.639896Z","bundle_sha256":"a1037cf6e2de2f6cd8cc94bc9fd1bac00a4d5a916e8257e97ffb4c3da2516b61"}}