{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:E23DKZ6UAFXODEFHO6SWHTYRDV","short_pith_number":"pith:E23DKZ6U","schema_version":"1.0","canonical_sha256":"26b63567d4016ee190a777a563cf111d7c550586c81307dbaec8ec11311682a0","source":{"kind":"arxiv","id":"1712.08125","version":1},"attestation_state":"computed","paper":{"title":"Unifying Map and Landmark Based Representations for Visual Navigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.RO"],"primary_cat":"cs.CV","authors_text":"David Fouhey, Jitendra Malik, Saurabh Gupta, Sergey Levine","submitted_at":"2017-12-21T18:02:14Z","abstract_excerpt":"This works presents a formulation for visual navigation that unifies map based spatial reasoning and path planning, with landmark based robust plan execution in noisy environments. Our proposed formulation is learned from data and is thus able to leverage statistical regularities of the world. This allows it to efficiently navigate in novel environments given only a sparse set of registered images as input for building representations for space. Our formulation is based on three key ideas: a learned path planner that outputs path plans to reach the goal, a feature synthesis engine that predict"},"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":"1712.08125","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-21T18:02:14Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"e7481fc25fb56a085c1b0462af48c4190944d0528e90cab4c7f56005b89174aa","abstract_canon_sha256":"5413c7100f5eb4a496d02ceb6533c7b5231f5ff1e7d949303f7af8bb2432d998"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:27:28.724329Z","signature_b64":"7MsjnnegWryzPIp0MxxJ+xztRpLjmTd2YokIsbRVGeQOjqHs61omXvoy7wlKsCvxB/R198j7LaklPJ5blmxoCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"26b63567d4016ee190a777a563cf111d7c550586c81307dbaec8ec11311682a0","last_reissued_at":"2026-05-18T00:27:28.723657Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:27:28.723657Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Unifying Map and Landmark Based Representations for Visual Navigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.RO"],"primary_cat":"cs.CV","authors_text":"David Fouhey, Jitendra Malik, Saurabh Gupta, Sergey Levine","submitted_at":"2017-12-21T18:02:14Z","abstract_excerpt":"This works presents a formulation for visual navigation that unifies map based spatial reasoning and path planning, with landmark based robust plan execution in noisy environments. Our proposed formulation is learned from data and is thus able to leverage statistical regularities of the world. This allows it to efficiently navigate in novel environments given only a sparse set of registered images as input for building representations for space. Our formulation is based on three key ideas: a learned path planner that outputs path plans to reach the goal, a feature synthesis engine that predict"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.08125","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1712.08125","created_at":"2026-05-18T00:27:28.723750+00:00"},{"alias_kind":"arxiv_version","alias_value":"1712.08125v1","created_at":"2026-05-18T00:27:28.723750+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.08125","created_at":"2026-05-18T00:27:28.723750+00:00"},{"alias_kind":"pith_short_12","alias_value":"E23DKZ6UAFXO","created_at":"2026-05-18T12:31:12.930513+00:00"},{"alias_kind":"pith_short_16","alias_value":"E23DKZ6UAFXODEFH","created_at":"2026-05-18T12:31:12.930513+00:00"},{"alias_kind":"pith_short_8","alias_value":"E23DKZ6U","created_at":"2026-05-18T12:31:12.930513+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":2,"sample":[{"citing_arxiv_id":"1906.11407","citing_title":"Emergence of Exploratory Look-Around Behaviors through Active Observation Completion","ref_index":28,"is_internal_anchor":true},{"citing_arxiv_id":"1907.11770","citing_title":"To Learn or Not to Learn: Analyzing the Role of Learning for Navigation in Virtual Environments","ref_index":12,"is_internal_anchor":true},{"citing_arxiv_id":"1807.06757","citing_title":"On Evaluation of Embodied Navigation Agents","ref_index":13,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/E23DKZ6UAFXODEFHO6SWHTYRDV","json":"https://pith.science/pith/E23DKZ6UAFXODEFHO6SWHTYRDV.json","graph_json":"https://pith.science/api/pith-number/E23DKZ6UAFXODEFHO6SWHTYRDV/graph.json","events_json":"https://pith.science/api/pith-number/E23DKZ6UAFXODEFHO6SWHTYRDV/events.json","paper":"https://pith.science/paper/E23DKZ6U"},"agent_actions":{"view_html":"https://pith.science/pith/E23DKZ6UAFXODEFHO6SWHTYRDV","download_json":"https://pith.science/pith/E23DKZ6UAFXODEFHO6SWHTYRDV.json","view_paper":"https://pith.science/paper/E23DKZ6U","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1712.08125&json=true","fetch_graph":"https://pith.science/api/pith-number/E23DKZ6UAFXODEFHO6SWHTYRDV/graph.json","fetch_events":"https://pith.science/api/pith-number/E23DKZ6UAFXODEFHO6SWHTYRDV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/E23DKZ6UAFXODEFHO6SWHTYRDV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/E23DKZ6UAFXODEFHO6SWHTYRDV/action/storage_attestation","attest_author":"https://pith.science/pith/E23DKZ6UAFXODEFHO6SWHTYRDV/action/author_attestation","sign_citation":"https://pith.science/pith/E23DKZ6UAFXODEFHO6SWHTYRDV/action/citation_signature","submit_replication":"https://pith.science/pith/E23DKZ6UAFXODEFHO6SWHTYRDV/action/replication_record"}},"created_at":"2026-05-18T00:27:28.723750+00:00","updated_at":"2026-05-18T00:27:28.723750+00:00"}