{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:XGXWCPLIHEOKOZL73F5CXZUWRH","short_pith_number":"pith:XGXWCPLI","canonical_record":{"source":{"id":"2011.06252","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-12T08:17:21Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"078a4e39fffa87909194aa537bcf55699f2c61c0a47a2d0a76ecbbbc472ff425","abstract_canon_sha256":"343ede53ab4cdaccb9521d28067b90fcd1dce7259d2b3c5d089672f9f23e0694"},"schema_version":"1.0"},"canonical_sha256":"b9af613d68391ca7657fd97a2be69689ec92e39e15426e2b4d6858a8ca2dc4f8","source":{"kind":"arxiv","id":"2011.06252","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.06252","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"arxiv_version","alias_value":"2011.06252v2","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.06252","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"pith_short_12","alias_value":"XGXWCPLIHEOK","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"pith_short_16","alias_value":"XGXWCPLIHEOKOZL7","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"pith_short_8","alias_value":"XGXWCPLI","created_at":"2026-07-05T04:14:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:XGXWCPLIHEOKOZL73F5CXZUWRH","target":"record","payload":{"canonical_record":{"source":{"id":"2011.06252","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-12T08:17:21Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"078a4e39fffa87909194aa537bcf55699f2c61c0a47a2d0a76ecbbbc472ff425","abstract_canon_sha256":"343ede53ab4cdaccb9521d28067b90fcd1dce7259d2b3c5d089672f9f23e0694"},"schema_version":"1.0"},"canonical_sha256":"b9af613d68391ca7657fd97a2be69689ec92e39e15426e2b4d6858a8ca2dc4f8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:14:36.235833Z","signature_b64":"+aLhCe1kOtKdNZ8IAqVgbjUpEc3svYTLyiGlILIHUEM884TL4qi4qDne9GQ4zEO09bi4UqZvqOEhWwMDEzRsDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9af613d68391ca7657fd97a2be69689ec92e39e15426e2b4d6858a8ca2dc4f8","last_reissued_at":"2026-07-05T04:14:36.235274Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:14:36.235274Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.06252","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:14:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L2SSnENfSMzoqEBcZwuOaoxndtiLqOKq23FPO8QMKYcSI2YbGAigGuiPv656f4F7bdopHhJGrzLdmn/Xztz6AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T01:04:33.038966Z"},"content_sha256":"70b7e6ce642f0e1e69dc0db7e946ebd3e7e9d1f7aca9f80a250e547c1c159073","schema_version":"1.0","event_id":"sha256:70b7e6ce642f0e1e69dc0db7e946ebd3e7e9d1f7aca9f80a250e547c1c159073"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:XGXWCPLIHEOKOZL73F5CXZUWRH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.RO"],"primary_cat":"cs.CV","authors_text":"Junaed Sattar, Md Jahidul Islam, Ruobing Wang","submitted_at":"2020-11-12T08:17:21Z","abstract_excerpt":"This paper presents a holistic approach to saliency-guided visual attention modeling (SVAM) for use by autonomous underwater robots. Our proposed model, named SVAM-Net, integrates deep visual features at various scales and semantics for effective salient object detection (SOD) in natural underwater images. The SVAM-Net architecture is configured in a unique way to jointly accommodate bottom-up and top-down learning within two separate branches of the network while sharing the same encoding layers. We design dedicated spatial attention modules (SAMs) along these learning pathways to exploit the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.06252","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2011.06252/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:14:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ycgujo1895M2N+K6G5cTzuHCfShmYksInqaSiWES+i8GtOfUN2q7wtnk9EASaRfMVShgHCOec5gSWChsAQ0BAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T01:04:33.039608Z"},"content_sha256":"ba5649eccc892fa49672bb5bbb5e1ce7294503ffa7e751ef34da5dbf30eed2e6","schema_version":"1.0","event_id":"sha256:ba5649eccc892fa49672bb5bbb5e1ce7294503ffa7e751ef34da5dbf30eed2e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XGXWCPLIHEOKOZL73F5CXZUWRH/bundle.json","state_url":"https://pith.science/pith/XGXWCPLIHEOKOZL73F5CXZUWRH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XGXWCPLIHEOKOZL73F5CXZUWRH/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-23T01:04:33Z","links":{"resolver":"https://pith.science/pith/XGXWCPLIHEOKOZL73F5CXZUWRH","bundle":"https://pith.science/pith/XGXWCPLIHEOKOZL73F5CXZUWRH/bundle.json","state":"https://pith.science/pith/XGXWCPLIHEOKOZL73F5CXZUWRH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XGXWCPLIHEOKOZL73F5CXZUWRH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:XGXWCPLIHEOKOZL73F5CXZUWRH","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"343ede53ab4cdaccb9521d28067b90fcd1dce7259d2b3c5d089672f9f23e0694","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-12T08:17:21Z","title_canon_sha256":"078a4e39fffa87909194aa537bcf55699f2c61c0a47a2d0a76ecbbbc472ff425"},"schema_version":"1.0","source":{"id":"2011.06252","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.06252","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"arxiv_version","alias_value":"2011.06252v2","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.06252","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"pith_short_12","alias_value":"XGXWCPLIHEOK","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"pith_short_16","alias_value":"XGXWCPLIHEOKOZL7","created_at":"2026-07-05T04:14:36Z"},{"alias_kind":"pith_short_8","alias_value":"XGXWCPLI","created_at":"2026-07-05T04:14:36Z"}],"graph_snapshots":[{"event_id":"sha256:ba5649eccc892fa49672bb5bbb5e1ce7294503ffa7e751ef34da5dbf30eed2e6","target":"graph","created_at":"2026-07-05T04:14:36Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2011.06252/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper presents a holistic approach to saliency-guided visual attention modeling (SVAM) for use by autonomous underwater robots. Our proposed model, named SVAM-Net, integrates deep visual features at various scales and semantics for effective salient object detection (SOD) in natural underwater images. The SVAM-Net architecture is configured in a unique way to jointly accommodate bottom-up and top-down learning within two separate branches of the network while sharing the same encoding layers. We design dedicated spatial attention modules (SAMs) along these learning pathways to exploit the","authors_text":"Junaed Sattar, Md Jahidul Islam, Ruobing Wang","cross_cats":["cs.LG","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-12T08:17:21Z","title":"SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.06252","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:70b7e6ce642f0e1e69dc0db7e946ebd3e7e9d1f7aca9f80a250e547c1c159073","target":"record","created_at":"2026-07-05T04:14:36Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"343ede53ab4cdaccb9521d28067b90fcd1dce7259d2b3c5d089672f9f23e0694","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-11-12T08:17:21Z","title_canon_sha256":"078a4e39fffa87909194aa537bcf55699f2c61c0a47a2d0a76ecbbbc472ff425"},"schema_version":"1.0","source":{"id":"2011.06252","kind":"arxiv","version":2}},"canonical_sha256":"b9af613d68391ca7657fd97a2be69689ec92e39e15426e2b4d6858a8ca2dc4f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b9af613d68391ca7657fd97a2be69689ec92e39e15426e2b4d6858a8ca2dc4f8","first_computed_at":"2026-07-05T04:14:36.235274Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:14:36.235274Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+aLhCe1kOtKdNZ8IAqVgbjUpEc3svYTLyiGlILIHUEM884TL4qi4qDne9GQ4zEO09bi4UqZvqOEhWwMDEzRsDA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:14:36.235833Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.06252","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:70b7e6ce642f0e1e69dc0db7e946ebd3e7e9d1f7aca9f80a250e547c1c159073","sha256:ba5649eccc892fa49672bb5bbb5e1ce7294503ffa7e751ef34da5dbf30eed2e6"],"state_sha256":"2d7a584306c761c44432c0d58c8e44d5648780e303917f5ded083d088810eb2f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ohV/dAE35/A2VMZzAysnX6P1xq1FFAX5elYSMBqFsueOHUTsKUqonKlg19V40meAZK7nTS90XvD5S0Py/IA4Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T01:04:33.045127Z","bundle_sha256":"034024c3c7e3aa234e2c563826f562c9a2a1274e14aff095ef76be483aa83cdb"}}