{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:U4XGBTCSEKRCTU7FHTQVHK5WO3","short_pith_number":"pith:U4XGBTCS","schema_version":"1.0","canonical_sha256":"a72e60cc5222a229d3e53ce153abb676d226156d074aca9b26bf7b5a56ad0a0a","source":{"kind":"arxiv","id":"1812.03402","version":2},"attestation_state":"computed","paper":{"title":"Semantically-Aware Attentive Neural Embeddings for Image-based Visual Localization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Han-Pang Chiu, Karan Sikka, Rakesh Kumar, Supun Samarasekera, Zachary Seymour","submitted_at":"2018-12-08T22:57:17Z","abstract_excerpt":"We present an approach that combines appearance and semantic information for 2D image-based localization (2D-VL) across large perceptual changes and time lags. Compared to appearance features, the semantic layout of a scene is generally more invariant to appearance variations. We use this intuition and propose a novel end-to-end deep attention-based framework that utilizes multimodal cues to generate robust embeddings for 2D-VL. The proposed attention module predicts a shared channel attention and modality-specific spatial attentions to guide the embeddings to focus on more reliable image regi"},"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":"1812.03402","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-08T22:57:17Z","cross_cats_sorted":[],"title_canon_sha256":"79e732580bf2225f2cdc4b501ec6c7f78d947faaf701fcf53497513efa48c8a2","abstract_canon_sha256":"ad333c0f98fcd86e52eb038140ca189f1de269c6d3859d2604d6a7c421bb0a6d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:36.743589Z","signature_b64":"DlQIBcCtaGa7XNf0867qC0gceggyOn+wnhov/OHm6JblRs85PPp+A/dOf40ZOErgYbKspJVc3ijpbGerb47MBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a72e60cc5222a229d3e53ce153abb676d226156d074aca9b26bf7b5a56ad0a0a","last_reissued_at":"2026-05-17T23:41:36.742383Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:36.742383Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Semantically-Aware Attentive Neural Embeddings for Image-based Visual Localization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Han-Pang Chiu, Karan Sikka, Rakesh Kumar, Supun Samarasekera, Zachary Seymour","submitted_at":"2018-12-08T22:57:17Z","abstract_excerpt":"We present an approach that combines appearance and semantic information for 2D image-based localization (2D-VL) across large perceptual changes and time lags. Compared to appearance features, the semantic layout of a scene is generally more invariant to appearance variations. We use this intuition and propose a novel end-to-end deep attention-based framework that utilizes multimodal cues to generate robust embeddings for 2D-VL. The proposed attention module predicts a shared channel attention and modality-specific spatial attentions to guide the embeddings to focus on more reliable image regi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.03402","kind":"arxiv","version":2},"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":"1812.03402","created_at":"2026-05-17T23:41:36.742516+00:00"},{"alias_kind":"arxiv_version","alias_value":"1812.03402v2","created_at":"2026-05-17T23:41:36.742516+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.03402","created_at":"2026-05-17T23:41:36.742516+00:00"},{"alias_kind":"pith_short_12","alias_value":"U4XGBTCSEKRC","created_at":"2026-05-18T12:32:56.356000+00:00"},{"alias_kind":"pith_short_16","alias_value":"U4XGBTCSEKRCTU7F","created_at":"2026-05-18T12:32:56.356000+00:00"},{"alias_kind":"pith_short_8","alias_value":"U4XGBTCS","created_at":"2026-05-18T12:32:56.356000+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/U4XGBTCSEKRCTU7FHTQVHK5WO3","json":"https://pith.science/pith/U4XGBTCSEKRCTU7FHTQVHK5WO3.json","graph_json":"https://pith.science/api/pith-number/U4XGBTCSEKRCTU7FHTQVHK5WO3/graph.json","events_json":"https://pith.science/api/pith-number/U4XGBTCSEKRCTU7FHTQVHK5WO3/events.json","paper":"https://pith.science/paper/U4XGBTCS"},"agent_actions":{"view_html":"https://pith.science/pith/U4XGBTCSEKRCTU7FHTQVHK5WO3","download_json":"https://pith.science/pith/U4XGBTCSEKRCTU7FHTQVHK5WO3.json","view_paper":"https://pith.science/paper/U4XGBTCS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1812.03402&json=true","fetch_graph":"https://pith.science/api/pith-number/U4XGBTCSEKRCTU7FHTQVHK5WO3/graph.json","fetch_events":"https://pith.science/api/pith-number/U4XGBTCSEKRCTU7FHTQVHK5WO3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/U4XGBTCSEKRCTU7FHTQVHK5WO3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/U4XGBTCSEKRCTU7FHTQVHK5WO3/action/storage_attestation","attest_author":"https://pith.science/pith/U4XGBTCSEKRCTU7FHTQVHK5WO3/action/author_attestation","sign_citation":"https://pith.science/pith/U4XGBTCSEKRCTU7FHTQVHK5WO3/action/citation_signature","submit_replication":"https://pith.science/pith/U4XGBTCSEKRCTU7FHTQVHK5WO3/action/replication_record"}},"created_at":"2026-05-17T23:41:36.742516+00:00","updated_at":"2026-05-17T23:41:36.742516+00:00"}