{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:XAJ7V2245OODWOXKNOMYQTLHAV","short_pith_number":"pith:XAJ7V224","schema_version":"1.0","canonical_sha256":"b813faeb5ceb9c3b3aea6b99884d67057441e4af3008c0fd45fb748f6886e07c","source":{"kind":"arxiv","id":"1710.00132","version":3},"attestation_state":"computed","paper":{"title":"Dense RGB-D semantic mapping with Pixel-Voxel neural network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cheng Zhao, Li Sun, Pulak Purkait, Rustam Stolkin","submitted_at":"2017-09-30T01:10:53Z","abstract_excerpt":"For intelligent robotics applications, extending 3D mapping to 3D semantic mapping enables robots to, not only localize themselves with respect to the scene's geometrical features but also simultaneously understand the higher level meaning of the scene contexts. Most previous methods focus on geometric 3D reconstruction and scene understanding independently notwithstanding the fact that joint estimation can boost the accuracy of the semantic mapping. In this paper, a dense RGB-D semantic mapping system with a Pixel-Voxel network is proposed, which can perform dense 3D mapping while simultaneou"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1710.00132","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-30T01:10:53Z","cross_cats_sorted":[],"title_canon_sha256":"cf27587f56d4c64047f21dfb9a26d1a259d0daa725075a84af4753878b8f3cfd","abstract_canon_sha256":"3ba419af4b5e745e79264a31827021a37734fd66c1b37b8ce03e462b89d48560"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:33:38.719544Z","signature_b64":"PUjv8eruxHaD2jVVf6nu0pFyTgM8EqpaySqw2xROC/lAROo01FRsA5RpiSkC+j5/tvLi/V2aZnbWA6QhCmevDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b813faeb5ceb9c3b3aea6b99884d67057441e4af3008c0fd45fb748f6886e07c","last_reissued_at":"2026-05-18T00:33:38.719118Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:33:38.719118Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dense RGB-D semantic mapping with Pixel-Voxel neural network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cheng Zhao, Li Sun, Pulak Purkait, Rustam Stolkin","submitted_at":"2017-09-30T01:10:53Z","abstract_excerpt":"For intelligent robotics applications, extending 3D mapping to 3D semantic mapping enables robots to, not only localize themselves with respect to the scene's geometrical features but also simultaneously understand the higher level meaning of the scene contexts. Most previous methods focus on geometric 3D reconstruction and scene understanding independently notwithstanding the fact that joint estimation can boost the accuracy of the semantic mapping. In this paper, a dense RGB-D semantic mapping system with a Pixel-Voxel network is proposed, which can perform dense 3D mapping while simultaneou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.00132","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1710.00132","created_at":"2026-05-18T00:33:38.719181+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.00132v3","created_at":"2026-05-18T00:33:38.719181+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.00132","created_at":"2026-05-18T00:33:38.719181+00:00"},{"alias_kind":"pith_short_12","alias_value":"XAJ7V2245OOD","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_16","alias_value":"XAJ7V2245OODWOXK","created_at":"2026-05-18T12:31:53.515858+00:00"},{"alias_kind":"pith_short_8","alias_value":"XAJ7V224","created_at":"2026-05-18T12:31:53.515858+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XAJ7V2245OODWOXKNOMYQTLHAV","json":"https://pith.science/pith/XAJ7V2245OODWOXKNOMYQTLHAV.json","graph_json":"https://pith.science/api/pith-number/XAJ7V2245OODWOXKNOMYQTLHAV/graph.json","events_json":"https://pith.science/api/pith-number/XAJ7V2245OODWOXKNOMYQTLHAV/events.json","paper":"https://pith.science/paper/XAJ7V224"},"agent_actions":{"view_html":"https://pith.science/pith/XAJ7V2245OODWOXKNOMYQTLHAV","download_json":"https://pith.science/pith/XAJ7V2245OODWOXKNOMYQTLHAV.json","view_paper":"https://pith.science/paper/XAJ7V224","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.00132&json=true","fetch_graph":"https://pith.science/api/pith-number/XAJ7V2245OODWOXKNOMYQTLHAV/graph.json","fetch_events":"https://pith.science/api/pith-number/XAJ7V2245OODWOXKNOMYQTLHAV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XAJ7V2245OODWOXKNOMYQTLHAV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XAJ7V2245OODWOXKNOMYQTLHAV/action/storage_attestation","attest_author":"https://pith.science/pith/XAJ7V2245OODWOXKNOMYQTLHAV/action/author_attestation","sign_citation":"https://pith.science/pith/XAJ7V2245OODWOXKNOMYQTLHAV/action/citation_signature","submit_replication":"https://pith.science/pith/XAJ7V2245OODWOXKNOMYQTLHAV/action/replication_record"}},"created_at":"2026-05-18T00:33:38.719181+00:00","updated_at":"2026-05-18T00:33:38.719181+00:00"}