{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:F5NWKN6THJF4THT7CDTT2IFAIF","short_pith_number":"pith:F5NWKN6T","canonical_record":{"source":{"id":"1211.1752","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2012-11-08T03:11:53Z","cross_cats_sorted":[],"title_canon_sha256":"bc76dce5941d4da5f31f4452507a520415bd254c43b90d462468169783c6f932","abstract_canon_sha256":"51f50b1ffdd875b1d62a52c05d057869e838db39420ab6a5a438422a3dc256db"},"schema_version":"1.0"},"canonical_sha256":"2f5b6537d33a4bc99e7f10e73d20a0416a9f0d2d3aebc777f1ed5da04405c274","source":{"kind":"arxiv","id":"1211.1752","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1211.1752","created_at":"2026-05-18T03:41:19Z"},{"alias_kind":"arxiv_version","alias_value":"1211.1752v1","created_at":"2026-05-18T03:41:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1211.1752","created_at":"2026-05-18T03:41:19Z"},{"alias_kind":"pith_short_12","alias_value":"F5NWKN6THJF4","created_at":"2026-05-18T12:27:04Z"},{"alias_kind":"pith_short_16","alias_value":"F5NWKN6THJF4THT7","created_at":"2026-05-18T12:27:04Z"},{"alias_kind":"pith_short_8","alias_value":"F5NWKN6T","created_at":"2026-05-18T12:27:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:F5NWKN6THJF4THT7CDTT2IFAIF","target":"record","payload":{"canonical_record":{"source":{"id":"1211.1752","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2012-11-08T03:11:53Z","cross_cats_sorted":[],"title_canon_sha256":"bc76dce5941d4da5f31f4452507a520415bd254c43b90d462468169783c6f932","abstract_canon_sha256":"51f50b1ffdd875b1d62a52c05d057869e838db39420ab6a5a438422a3dc256db"},"schema_version":"1.0"},"canonical_sha256":"2f5b6537d33a4bc99e7f10e73d20a0416a9f0d2d3aebc777f1ed5da04405c274","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:41:19.621117Z","signature_b64":"+b9HcWwLNBajs/66TI9qYvguucLw7iaI3wVb4TAAhCX0ANSX9bcdTViG8iFO+MCxA6YluZJ/sbWfwRPeIaUMAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2f5b6537d33a4bc99e7f10e73d20a0416a9f0d2d3aebc777f1ed5da04405c274","last_reissued_at":"2026-05-18T03:41:19.620707Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:41:19.620707Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1211.1752","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":"2026-05-18T03:41:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JE0kA4+4FTJ4WhFq79AnLmqGilhX8S27AJH+a3aIwSyX141FwdBdiVJuTw9SVW9BXD910Re42I7frULgQcE+Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T01:21:06.871470Z"},"content_sha256":"7947dd179f7fe67424044862ede8fe6430857033433c3cfffb8739cdd7aad8c1","schema_version":"1.0","event_id":"sha256:7947dd179f7fe67424044862ede8fe6430857033433c3cfffb8739cdd7aad8c1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:F5NWKN6THJF4THT7CDTT2IFAIF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"3D Scene Grammar for Parsing RGB-D Pointclouds","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abhishek Anand, Sherwin Li","submitted_at":"2012-11-08T03:11:53Z","abstract_excerpt":"We pose 3D scene-understanding as a problem of parsing in a grammar. A grammar helps us capture the compositional structure of real-word objects, e.g., a chair is composed of a seat, a back-rest and some legs. Having multiple rules for an object helps us capture structural variations in objects, e.g., a chair can optionally also have arm-rests. Finally, having rules to capture composition at different levels helps us formulate the entire scene-processing pipeline as a single problem of finding most likely parse-tree---small segments combine to form parts of objects, parts to objects and object"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1211.1752","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":"2026-05-18T03:41:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"soSrVUy/lx7XsRN/6IabAC6T96z477KTWh+puDEAqbD2VHEEABZG9rbJgsyN8AOktRgHdDyREmobQKPXfrIZBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T01:21:06.872130Z"},"content_sha256":"6619bbed581b44365446845219ab16e4c12b42ad8eee9d8cc469aa3b1e998425","schema_version":"1.0","event_id":"sha256:6619bbed581b44365446845219ab16e4c12b42ad8eee9d8cc469aa3b1e998425"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/F5NWKN6THJF4THT7CDTT2IFAIF/bundle.json","state_url":"https://pith.science/pith/F5NWKN6THJF4THT7CDTT2IFAIF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/F5NWKN6THJF4THT7CDTT2IFAIF/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":"2026-05-26T01:21:06Z","links":{"resolver":"https://pith.science/pith/F5NWKN6THJF4THT7CDTT2IFAIF","bundle":"https://pith.science/pith/F5NWKN6THJF4THT7CDTT2IFAIF/bundle.json","state":"https://pith.science/pith/F5NWKN6THJF4THT7CDTT2IFAIF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/F5NWKN6THJF4THT7CDTT2IFAIF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:F5NWKN6THJF4THT7CDTT2IFAIF","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":"51f50b1ffdd875b1d62a52c05d057869e838db39420ab6a5a438422a3dc256db","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2012-11-08T03:11:53Z","title_canon_sha256":"bc76dce5941d4da5f31f4452507a520415bd254c43b90d462468169783c6f932"},"schema_version":"1.0","source":{"id":"1211.1752","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1211.1752","created_at":"2026-05-18T03:41:19Z"},{"alias_kind":"arxiv_version","alias_value":"1211.1752v1","created_at":"2026-05-18T03:41:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1211.1752","created_at":"2026-05-18T03:41:19Z"},{"alias_kind":"pith_short_12","alias_value":"F5NWKN6THJF4","created_at":"2026-05-18T12:27:04Z"},{"alias_kind":"pith_short_16","alias_value":"F5NWKN6THJF4THT7","created_at":"2026-05-18T12:27:04Z"},{"alias_kind":"pith_short_8","alias_value":"F5NWKN6T","created_at":"2026-05-18T12:27:04Z"}],"graph_snapshots":[{"event_id":"sha256:6619bbed581b44365446845219ab16e4c12b42ad8eee9d8cc469aa3b1e998425","target":"graph","created_at":"2026-05-18T03:41:19Z","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":"We pose 3D scene-understanding as a problem of parsing in a grammar. A grammar helps us capture the compositional structure of real-word objects, e.g., a chair is composed of a seat, a back-rest and some legs. Having multiple rules for an object helps us capture structural variations in objects, e.g., a chair can optionally also have arm-rests. Finally, having rules to capture composition at different levels helps us formulate the entire scene-processing pipeline as a single problem of finding most likely parse-tree---small segments combine to form parts of objects, parts to objects and object","authors_text":"Abhishek Anand, Sherwin Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2012-11-08T03:11:53Z","title":"3D Scene Grammar for Parsing RGB-D Pointclouds"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1211.1752","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":"sha256:7947dd179f7fe67424044862ede8fe6430857033433c3cfffb8739cdd7aad8c1","target":"record","created_at":"2026-05-18T03:41:19Z","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":"51f50b1ffdd875b1d62a52c05d057869e838db39420ab6a5a438422a3dc256db","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2012-11-08T03:11:53Z","title_canon_sha256":"bc76dce5941d4da5f31f4452507a520415bd254c43b90d462468169783c6f932"},"schema_version":"1.0","source":{"id":"1211.1752","kind":"arxiv","version":1}},"canonical_sha256":"2f5b6537d33a4bc99e7f10e73d20a0416a9f0d2d3aebc777f1ed5da04405c274","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2f5b6537d33a4bc99e7f10e73d20a0416a9f0d2d3aebc777f1ed5da04405c274","first_computed_at":"2026-05-18T03:41:19.620707Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:41:19.620707Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+b9HcWwLNBajs/66TI9qYvguucLw7iaI3wVb4TAAhCX0ANSX9bcdTViG8iFO+MCxA6YluZJ/sbWfwRPeIaUMAg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:41:19.621117Z","signed_message":"canonical_sha256_bytes"},"source_id":"1211.1752","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7947dd179f7fe67424044862ede8fe6430857033433c3cfffb8739cdd7aad8c1","sha256:6619bbed581b44365446845219ab16e4c12b42ad8eee9d8cc469aa3b1e998425"],"state_sha256":"972a0945e355c4a4f0e2865c3b9fba5b8d4258435202505931cbd031d2649e50"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Sc4cz6YTqUzhFK1fqEbQYtgMigKHL6zr1v/dDc+KUXaF286wkc2bHB+1JqUR5W2LApU+hDvxEl+cLLOBDMM+CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T01:21:06.875573Z","bundle_sha256":"91aa8430887b2be735ac6a79940d36f991f2b598530c53710b221d29d932b07e"}}