{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:NBHHCMB7K4GZOXVSMD2BCZAZHO","short_pith_number":"pith:NBHHCMB7","schema_version":"1.0","canonical_sha256":"684e71303f570d975eb260f41164193b856b278903d7fdee02016153c2a18338","source":{"kind":"arxiv","id":"1708.01447","version":3},"attestation_state":"computed","paper":{"title":"Video Salient Object Detection Using Spatiotemporal Deep Features","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Akihiro Sugimoto, Trung-Nghia Le","submitted_at":"2017-08-04T11:05:14Z","abstract_excerpt":"This paper presents a method for detecting salient objects in videos where temporal information in addition to spatial information is fully taken into account. Following recent reports on the advantage of deep features over conventional hand-crafted features, we propose a new set of SpatioTemporal Deep (STD) features that utilize local and global contexts over frames. We also propose new SpatioTemporal Conditional Random Field (STCRF) to compute saliency from STD features. STCRF is our extension of CRF to the temporal domain and describes the relationships among neighboring regions both in a f"},"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":"1708.01447","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-04T11:05:14Z","cross_cats_sorted":[],"title_canon_sha256":"c5d9ffc9c2676269b9c63119fb6e52d9804c367c99ab820f831544f06f434d79","abstract_canon_sha256":"21afbb5502cc109f9eb453408616cbe83d3e2277b86fbe17e436756cea1a6f59"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:20.067280Z","signature_b64":"2A+P5eigDMvDycqGXBOBTnuvJyw3wJA/vFCgFZlOILwn08eSC6Ka44D+RkcoVX4Tzs5V2Clmbw72Vp7z72d/AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"684e71303f570d975eb260f41164193b856b278903d7fdee02016153c2a18338","last_reissued_at":"2026-05-18T00:09:20.066731Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:20.066731Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Video Salient Object Detection Using Spatiotemporal Deep Features","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Akihiro Sugimoto, Trung-Nghia Le","submitted_at":"2017-08-04T11:05:14Z","abstract_excerpt":"This paper presents a method for detecting salient objects in videos where temporal information in addition to spatial information is fully taken into account. Following recent reports on the advantage of deep features over conventional hand-crafted features, we propose a new set of SpatioTemporal Deep (STD) features that utilize local and global contexts over frames. We also propose new SpatioTemporal Conditional Random Field (STCRF) to compute saliency from STD features. STCRF is our extension of CRF to the temporal domain and describes the relationships among neighboring regions both in a f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01447","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":"1708.01447","created_at":"2026-05-18T00:09:20.066826+00:00"},{"alias_kind":"arxiv_version","alias_value":"1708.01447v3","created_at":"2026-05-18T00:09:20.066826+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01447","created_at":"2026-05-18T00:09:20.066826+00:00"},{"alias_kind":"pith_short_12","alias_value":"NBHHCMB7K4GZ","created_at":"2026-05-18T12:31:31.346846+00:00"},{"alias_kind":"pith_short_16","alias_value":"NBHHCMB7K4GZOXVS","created_at":"2026-05-18T12:31:31.346846+00:00"},{"alias_kind":"pith_short_8","alias_value":"NBHHCMB7","created_at":"2026-05-18T12:31:31.346846+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/NBHHCMB7K4GZOXVSMD2BCZAZHO","json":"https://pith.science/pith/NBHHCMB7K4GZOXVSMD2BCZAZHO.json","graph_json":"https://pith.science/api/pith-number/NBHHCMB7K4GZOXVSMD2BCZAZHO/graph.json","events_json":"https://pith.science/api/pith-number/NBHHCMB7K4GZOXVSMD2BCZAZHO/events.json","paper":"https://pith.science/paper/NBHHCMB7"},"agent_actions":{"view_html":"https://pith.science/pith/NBHHCMB7K4GZOXVSMD2BCZAZHO","download_json":"https://pith.science/pith/NBHHCMB7K4GZOXVSMD2BCZAZHO.json","view_paper":"https://pith.science/paper/NBHHCMB7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1708.01447&json=true","fetch_graph":"https://pith.science/api/pith-number/NBHHCMB7K4GZOXVSMD2BCZAZHO/graph.json","fetch_events":"https://pith.science/api/pith-number/NBHHCMB7K4GZOXVSMD2BCZAZHO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NBHHCMB7K4GZOXVSMD2BCZAZHO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NBHHCMB7K4GZOXVSMD2BCZAZHO/action/storage_attestation","attest_author":"https://pith.science/pith/NBHHCMB7K4GZOXVSMD2BCZAZHO/action/author_attestation","sign_citation":"https://pith.science/pith/NBHHCMB7K4GZOXVSMD2BCZAZHO/action/citation_signature","submit_replication":"https://pith.science/pith/NBHHCMB7K4GZOXVSMD2BCZAZHO/action/replication_record"}},"created_at":"2026-05-18T00:09:20.066826+00:00","updated_at":"2026-05-18T00:09:20.066826+00:00"}