{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:5Z4N3SD3KHTKL77UF74LW3PD7Z","short_pith_number":"pith:5Z4N3SD3","schema_version":"1.0","canonical_sha256":"ee78ddc87b51e6a5fff42ff8bb6de3fe589213bff3addaf3e473fc520d0741a5","source":{"kind":"arxiv","id":"1802.02534","version":3},"attestation_state":"computed","paper":{"title":"FixaTons: A collection of Human Fixations Datasets and Metrics for Scanpath Similarity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.AI","authors_text":"Alessandra Rufa, Dario Zanca, Francesca Rosini, Pietro Piu, Valeria Serchi","submitted_at":"2018-02-07T17:20:31Z","abstract_excerpt":"In the last three decades, human visual attention has been a topic of great interest in various disciplines. In computer vision, many models have been proposed to predict the distribution of human fixations on a visual stimulus. Recently, thanks to the creation of large collections of data, machine learning algorithms have obtained state-of-the-art performance on the task of saliency map estimation. On the other hand, computational models of scanpath are much less studied. Works are often only descriptive or task specific. This is due to the fact that the scanpath is harder to model because it"},"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":"1802.02534","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-02-07T17:20:31Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"216830b333727994ca1023548749268b96307f9767672a2f24f293cb407e5ab6","abstract_canon_sha256":"931e38a620929c71441eeefec261908edbfef60d5bd778e92df383a8740b277d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:13.299476Z","signature_b64":"ZV0wwFwtsBPEhCjIRemiF3Eos9Z1KZeoNvCXCsEXmSpqXMTx2dtw05eZcqTUyG13sx3TgLp8c0lPL9bKW9UnDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee78ddc87b51e6a5fff42ff8bb6de3fe589213bff3addaf3e473fc520d0741a5","last_reissued_at":"2026-05-18T00:04:13.298804Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:13.298804Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FixaTons: A collection of Human Fixations Datasets and Metrics for Scanpath Similarity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.AI","authors_text":"Alessandra Rufa, Dario Zanca, Francesca Rosini, Pietro Piu, Valeria Serchi","submitted_at":"2018-02-07T17:20:31Z","abstract_excerpt":"In the last three decades, human visual attention has been a topic of great interest in various disciplines. In computer vision, many models have been proposed to predict the distribution of human fixations on a visual stimulus. Recently, thanks to the creation of large collections of data, machine learning algorithms have obtained state-of-the-art performance on the task of saliency map estimation. On the other hand, computational models of scanpath are much less studied. Works are often only descriptive or task specific. This is due to the fact that the scanpath is harder to model because it"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.02534","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":"1802.02534","created_at":"2026-05-18T00:04:13.298898+00:00"},{"alias_kind":"arxiv_version","alias_value":"1802.02534v3","created_at":"2026-05-18T00:04:13.298898+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.02534","created_at":"2026-05-18T00:04:13.298898+00:00"},{"alias_kind":"pith_short_12","alias_value":"5Z4N3SD3KHTK","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_16","alias_value":"5Z4N3SD3KHTKL77U","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_8","alias_value":"5Z4N3SD3","created_at":"2026-05-18T12:32:08.215937+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/5Z4N3SD3KHTKL77UF74LW3PD7Z","json":"https://pith.science/pith/5Z4N3SD3KHTKL77UF74LW3PD7Z.json","graph_json":"https://pith.science/api/pith-number/5Z4N3SD3KHTKL77UF74LW3PD7Z/graph.json","events_json":"https://pith.science/api/pith-number/5Z4N3SD3KHTKL77UF74LW3PD7Z/events.json","paper":"https://pith.science/paper/5Z4N3SD3"},"agent_actions":{"view_html":"https://pith.science/pith/5Z4N3SD3KHTKL77UF74LW3PD7Z","download_json":"https://pith.science/pith/5Z4N3SD3KHTKL77UF74LW3PD7Z.json","view_paper":"https://pith.science/paper/5Z4N3SD3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1802.02534&json=true","fetch_graph":"https://pith.science/api/pith-number/5Z4N3SD3KHTKL77UF74LW3PD7Z/graph.json","fetch_events":"https://pith.science/api/pith-number/5Z4N3SD3KHTKL77UF74LW3PD7Z/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5Z4N3SD3KHTKL77UF74LW3PD7Z/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5Z4N3SD3KHTKL77UF74LW3PD7Z/action/storage_attestation","attest_author":"https://pith.science/pith/5Z4N3SD3KHTKL77UF74LW3PD7Z/action/author_attestation","sign_citation":"https://pith.science/pith/5Z4N3SD3KHTKL77UF74LW3PD7Z/action/citation_signature","submit_replication":"https://pith.science/pith/5Z4N3SD3KHTKL77UF74LW3PD7Z/action/replication_record"}},"created_at":"2026-05-18T00:04:13.298898+00:00","updated_at":"2026-05-18T00:04:13.298898+00:00"}