{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:CKVSR4333L6PKJLKBFX3L3RUYC","short_pith_number":"pith:CKVSR433","canonical_record":{"source":{"id":"2308.11417","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-22T13:02:23Z","cross_cats_sorted":[],"title_canon_sha256":"8af7e2cfe0d3c74109f97f4e2986736753d6217e9ca8b94a245ed7ff89fc4d62","abstract_canon_sha256":"31de6e9f5949ad5167105498e6d1a7645ae9ab6d00e6cc428bbfe3358f7d2229"},"schema_version":"1.0"},"canonical_sha256":"12ab28f37bdafcf5256a096fb5ee34c0914d133047cd7264e3a3d5bb99293989","source":{"kind":"arxiv","id":"2308.11417","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.11417","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"arxiv_version","alias_value":"2308.11417v1","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.11417","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"pith_short_12","alias_value":"CKVSR4333L6P","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"pith_short_16","alias_value":"CKVSR4333L6PKJLK","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"pith_short_8","alias_value":"CKVSR433","created_at":"2026-07-05T06:43:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:CKVSR4333L6PKJLKBFX3L3RUYC","target":"record","payload":{"canonical_record":{"source":{"id":"2308.11417","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-22T13:02:23Z","cross_cats_sorted":[],"title_canon_sha256":"8af7e2cfe0d3c74109f97f4e2986736753d6217e9ca8b94a245ed7ff89fc4d62","abstract_canon_sha256":"31de6e9f5949ad5167105498e6d1a7645ae9ab6d00e6cc428bbfe3358f7d2229"},"schema_version":"1.0"},"canonical_sha256":"12ab28f37bdafcf5256a096fb5ee34c0914d133047cd7264e3a3d5bb99293989","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:43:34.090432Z","signature_b64":"YBr1veNE56iHFMJzRkAusDufcnNzIGzTJk1SwwkkPt0SaOujMJnEtEAxgZu11B8EAr6iUeZttRcui3A4ZEgRAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"12ab28f37bdafcf5256a096fb5ee34c0914d133047cd7264e3a3d5bb99293989","last_reissued_at":"2026-07-05T06:43:34.089946Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:43:34.089946Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.11417","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":"2026-07-05T06:43:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bjU01Tf/CVUS6lfCDzqHqdzhaP2I86rArnCjjlymlPQqKIgUW4iKcKBv7uueDrh88hncrlH9WJODb2NVtyI+AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T02:41:06.846558Z"},"content_sha256":"0206de182765ddd199b90443e11951b2dc01b5cc5ac65d11e84ffebef93c3fdf","schema_version":"1.0","event_id":"sha256:0206de182765ddd199b90443e11951b2dc01b5cc5ac65d11e84ffebef93c3fdf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:CKVSR4333L6PKJLKBFX3L3RUYC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Angela Dai, Chandan Yeshwanth, Matthias Nie{\\ss}ner, Yueh-Cheng Liu","submitted_at":"2023-08-22T13:02:23Z","abstract_excerpt":"We present ScanNet++, a large-scale dataset that couples together capture of high-quality and commodity-level geometry and color of indoor scenes. Each scene is captured with a high-end laser scanner at sub-millimeter resolution, along with registered 33-megapixel images from a DSLR camera, and RGB-D streams from an iPhone. Scene reconstructions are further annotated with an open vocabulary of semantics, with label-ambiguous scenarios explicitly annotated for comprehensive semantic understanding. ScanNet++ enables a new real-world benchmark for novel view synthesis, both from high-quality RGB "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.11417","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/2308.11417/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":"2026-07-05T06:43:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OS95j3/BAd+3rZA0EyvfLKeAvAdxbSwlg6TwdjIPkSL2CJ1XMord8nFUyKHImfnB0YACazpvFBWOOtZ2pddgBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T02:41:06.846884Z"},"content_sha256":"9b0b044de44f01a8083001520d89416745ca4e4c40b464eccc9fce116ce34525","schema_version":"1.0","event_id":"sha256:9b0b044de44f01a8083001520d89416745ca4e4c40b464eccc9fce116ce34525"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CKVSR4333L6PKJLKBFX3L3RUYC/bundle.json","state_url":"https://pith.science/pith/CKVSR4333L6PKJLKBFX3L3RUYC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CKVSR4333L6PKJLKBFX3L3RUYC/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":"2026-08-14T02:41:06Z","links":{"resolver":"https://pith.science/pith/CKVSR4333L6PKJLKBFX3L3RUYC","bundle":"https://pith.science/pith/CKVSR4333L6PKJLKBFX3L3RUYC/bundle.json","state":"https://pith.science/pith/CKVSR4333L6PKJLKBFX3L3RUYC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CKVSR4333L6PKJLKBFX3L3RUYC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:CKVSR4333L6PKJLKBFX3L3RUYC","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":"31de6e9f5949ad5167105498e6d1a7645ae9ab6d00e6cc428bbfe3358f7d2229","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-22T13:02:23Z","title_canon_sha256":"8af7e2cfe0d3c74109f97f4e2986736753d6217e9ca8b94a245ed7ff89fc4d62"},"schema_version":"1.0","source":{"id":"2308.11417","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.11417","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"arxiv_version","alias_value":"2308.11417v1","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.11417","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"pith_short_12","alias_value":"CKVSR4333L6P","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"pith_short_16","alias_value":"CKVSR4333L6PKJLK","created_at":"2026-07-05T06:43:34Z"},{"alias_kind":"pith_short_8","alias_value":"CKVSR433","created_at":"2026-07-05T06:43:34Z"}],"graph_snapshots":[{"event_id":"sha256:9b0b044de44f01a8083001520d89416745ca4e4c40b464eccc9fce116ce34525","target":"graph","created_at":"2026-07-05T06:43:34Z","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/2308.11417/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present ScanNet++, a large-scale dataset that couples together capture of high-quality and commodity-level geometry and color of indoor scenes. Each scene is captured with a high-end laser scanner at sub-millimeter resolution, along with registered 33-megapixel images from a DSLR camera, and RGB-D streams from an iPhone. Scene reconstructions are further annotated with an open vocabulary of semantics, with label-ambiguous scenarios explicitly annotated for comprehensive semantic understanding. ScanNet++ enables a new real-world benchmark for novel view synthesis, both from high-quality RGB ","authors_text":"Angela Dai, Chandan Yeshwanth, Matthias Nie{\\ss}ner, Yueh-Cheng Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-22T13:02:23Z","title":"ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.11417","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":"sha256:0206de182765ddd199b90443e11951b2dc01b5cc5ac65d11e84ffebef93c3fdf","target":"record","created_at":"2026-07-05T06:43:34Z","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":"31de6e9f5949ad5167105498e6d1a7645ae9ab6d00e6cc428bbfe3358f7d2229","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-22T13:02:23Z","title_canon_sha256":"8af7e2cfe0d3c74109f97f4e2986736753d6217e9ca8b94a245ed7ff89fc4d62"},"schema_version":"1.0","source":{"id":"2308.11417","kind":"arxiv","version":1}},"canonical_sha256":"12ab28f37bdafcf5256a096fb5ee34c0914d133047cd7264e3a3d5bb99293989","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"12ab28f37bdafcf5256a096fb5ee34c0914d133047cd7264e3a3d5bb99293989","first_computed_at":"2026-07-05T06:43:34.089946Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:43:34.089946Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YBr1veNE56iHFMJzRkAusDufcnNzIGzTJk1SwwkkPt0SaOujMJnEtEAxgZu11B8EAr6iUeZttRcui3A4ZEgRAA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:43:34.090432Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.11417","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0206de182765ddd199b90443e11951b2dc01b5cc5ac65d11e84ffebef93c3fdf","sha256:9b0b044de44f01a8083001520d89416745ca4e4c40b464eccc9fce116ce34525"],"state_sha256":"80d4e97ab562970e3355fcdeeffb7e3e58f306f4b0b10c83e15b46983e312472"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IEhZ/jYNcDvsK7StTm+EtcQRglXSL93YEfM5XccFTBhuxTnEM3avRinsPcUwETDKko8UBBWuFxSmJI4HNf8OCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T02:41:06.849994Z","bundle_sha256":"c5865adc9bc4cf3c8d5110c9b00865380c4c6ed974303e104dcc89e210196be6"}}