{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:PVYODZZQFZE6F2SSFYJIUR2ANV","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":"dcf96f98002f03a1974d11075b10b026dd7c4f44d786abd98a648f83e0a14562","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-12-16T18:59:26Z","title_canon_sha256":"eda544093420278d7eccca4687be1a89e9f6a54e0731dba14adcf8ef27460100"},"schema_version":"1.0","source":{"id":"2012.09165","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.09165","created_at":"2026-07-05T02:52:27Z"},{"alias_kind":"arxiv_version","alias_value":"2012.09165v3","created_at":"2026-07-05T02:52:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.09165","created_at":"2026-07-05T02:52:27Z"},{"alias_kind":"pith_short_12","alias_value":"PVYODZZQFZE6","created_at":"2026-07-05T02:52:27Z"},{"alias_kind":"pith_short_16","alias_value":"PVYODZZQFZE6F2SS","created_at":"2026-07-05T02:52:27Z"},{"alias_kind":"pith_short_8","alias_value":"PVYODZZQ","created_at":"2026-07-05T02:52:27Z"}],"graph_snapshots":[{"event_id":"sha256:79b012773047b52b2f108ffd6b21708c2826d9436ad6f10fd3b6bd6770716ae9","target":"graph","created_at":"2026-07-05T02:52:27Z","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/2012.09165/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The rapid progress in 3D scene understanding has come with growing demand for data; however, collecting and annotating 3D scenes (e.g. point clouds) are notoriously hard. For example, the number of scenes (e.g. indoor rooms) that can be accessed and scanned might be limited; even given sufficient data, acquiring 3D labels (e.g. instance masks) requires intensive human labor. In this paper, we explore data-efficient learning for 3D point cloud. As a first step towards this direction, we propose Contrastive Scene Contexts, a 3D pre-training method that makes use of both point-level correspondenc","authors_text":"Benjamin Graham, Ji Hou, Matthias Nie{\\ss}ner, Saining Xie","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-12-16T18:59:26Z","title":"Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.09165","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:fbd96159abfc4005f48e63e9dbb6e377b169664675445fa9b01bd8daf9696a6c","target":"record","created_at":"2026-07-05T02:52:27Z","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":"dcf96f98002f03a1974d11075b10b026dd7c4f44d786abd98a648f83e0a14562","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-12-16T18:59:26Z","title_canon_sha256":"eda544093420278d7eccca4687be1a89e9f6a54e0731dba14adcf8ef27460100"},"schema_version":"1.0","source":{"id":"2012.09165","kind":"arxiv","version":3}},"canonical_sha256":"7d70e1e7302e49e2ea522e128a47406d797d2f3c551a101721333dc6e3900d30","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7d70e1e7302e49e2ea522e128a47406d797d2f3c551a101721333dc6e3900d30","first_computed_at":"2026-07-05T02:52:27.521827Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:52:27.521827Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"55ldtcUBaG5wduooQSCrbnfxJIUM9yOQDu2/l88FULF0ec/xTLQyruZPUd7TMp2yQ/3NHS70wkZrWZ1qrDYJBg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:52:27.522373Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.09165","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fbd96159abfc4005f48e63e9dbb6e377b169664675445fa9b01bd8daf9696a6c","sha256:79b012773047b52b2f108ffd6b21708c2826d9436ad6f10fd3b6bd6770716ae9"],"state_sha256":"127971e7babc69573d0eeda1cb447cae12ba8739cb3d5fb3e7b0ba4f7462f929"}