{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:CGANMF3O4IAULJKL3PQDWR5YP7","short_pith_number":"pith:CGANMF3O","schema_version":"1.0","canonical_sha256":"1180d6176ee20145a54bdbe03b47b87fca3eb69e9e64f1383c4143f754572c21","source":{"kind":"arxiv","id":"1807.01312","version":1},"attestation_state":"computed","paper":{"title":"Viewpoint Estimation-Insights & Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ayellet Tal, Gilad Divon","submitted_at":"2018-07-03T17:57:58Z","abstract_excerpt":"This paper addresses the problem of viewpoint estimation of an object in a given image. It presents five key insights that should be taken into consideration when designing a CNN that solves the problem. Based on these insights, the paper proposes a network in which (i) The architecture jointly solves detection, classification, and viewpoint estimation. (ii) New types of data are added and trained on. (iii) A novel loss function, which takes into account both the geometry of the problem and the new types of data, is propose. Our network improves the state-of-the-art results for this problem by"},"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":"1807.01312","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-03T17:57:58Z","cross_cats_sorted":[],"title_canon_sha256":"4e317dc9049348d04b6a76df809f8ce1a2af1dd39210564a24eefcbd2c01f052","abstract_canon_sha256":"145b228d2084888a6d31fca9822b8b075bf11deb605304f542c9a1847df55390"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:11:44.662814Z","signature_b64":"Z+QsY5lMBp9JbqgzHROOm9C2pcyHgSME+kRoT77ys+eNHYhifB7Avy0JcbY0i5of7kH2UXIBiGicXdVcasfRBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1180d6176ee20145a54bdbe03b47b87fca3eb69e9e64f1383c4143f754572c21","last_reissued_at":"2026-05-18T00:11:44.661845Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:11:44.661845Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Viewpoint Estimation-Insights & Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ayellet Tal, Gilad Divon","submitted_at":"2018-07-03T17:57:58Z","abstract_excerpt":"This paper addresses the problem of viewpoint estimation of an object in a given image. It presents five key insights that should be taken into consideration when designing a CNN that solves the problem. Based on these insights, the paper proposes a network in which (i) The architecture jointly solves detection, classification, and viewpoint estimation. (ii) New types of data are added and trained on. (iii) A novel loss function, which takes into account both the geometry of the problem and the new types of data, is propose. Our network improves the state-of-the-art results for this problem by"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.01312","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":"1807.01312","created_at":"2026-05-18T00:11:44.662010+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.01312v1","created_at":"2026-05-18T00:11:44.662010+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.01312","created_at":"2026-05-18T00:11:44.662010+00:00"},{"alias_kind":"pith_short_12","alias_value":"CGANMF3O4IAU","created_at":"2026-05-18T12:32:16.446611+00:00"},{"alias_kind":"pith_short_16","alias_value":"CGANMF3O4IAULJKL","created_at":"2026-05-18T12:32:16.446611+00:00"},{"alias_kind":"pith_short_8","alias_value":"CGANMF3O","created_at":"2026-05-18T12:32:16.446611+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/CGANMF3O4IAULJKL3PQDWR5YP7","json":"https://pith.science/pith/CGANMF3O4IAULJKL3PQDWR5YP7.json","graph_json":"https://pith.science/api/pith-number/CGANMF3O4IAULJKL3PQDWR5YP7/graph.json","events_json":"https://pith.science/api/pith-number/CGANMF3O4IAULJKL3PQDWR5YP7/events.json","paper":"https://pith.science/paper/CGANMF3O"},"agent_actions":{"view_html":"https://pith.science/pith/CGANMF3O4IAULJKL3PQDWR5YP7","download_json":"https://pith.science/pith/CGANMF3O4IAULJKL3PQDWR5YP7.json","view_paper":"https://pith.science/paper/CGANMF3O","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.01312&json=true","fetch_graph":"https://pith.science/api/pith-number/CGANMF3O4IAULJKL3PQDWR5YP7/graph.json","fetch_events":"https://pith.science/api/pith-number/CGANMF3O4IAULJKL3PQDWR5YP7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CGANMF3O4IAULJKL3PQDWR5YP7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CGANMF3O4IAULJKL3PQDWR5YP7/action/storage_attestation","attest_author":"https://pith.science/pith/CGANMF3O4IAULJKL3PQDWR5YP7/action/author_attestation","sign_citation":"https://pith.science/pith/CGANMF3O4IAULJKL3PQDWR5YP7/action/citation_signature","submit_replication":"https://pith.science/pith/CGANMF3O4IAULJKL3PQDWR5YP7/action/replication_record"}},"created_at":"2026-05-18T00:11:44.662010+00:00","updated_at":"2026-05-18T00:11:44.662010+00:00"}