{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:3Q2Y23IPIM2NYAFS3CFEA5MJAN","short_pith_number":"pith:3Q2Y23IP","canonical_record":{"source":{"id":"1803.08636","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-23T02:04:47Z","cross_cats_sorted":["cs.AI","cs.MM"],"title_canon_sha256":"a14a525148744aed511608b8732de0ec15fbdc68dc0f58f12ebad57a2460e4b0","abstract_canon_sha256":"00d4af9e4f600ab65384d82c123e49941970121af2119d4e59e001f77b03570c"},"schema_version":"1.0"},"canonical_sha256":"dc358d6d0f4334dc00b2d88a40758903572490cfab8a3a66d0b4e6c1a8f33e98","source":{"kind":"arxiv","id":"1803.08636","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.08636","created_at":"2026-05-18T00:03:29Z"},{"alias_kind":"arxiv_version","alias_value":"1803.08636v2","created_at":"2026-05-18T00:03:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.08636","created_at":"2026-05-18T00:03:29Z"},{"alias_kind":"pith_short_12","alias_value":"3Q2Y23IPIM2N","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"3Q2Y23IPIM2NYAFS","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"3Q2Y23IP","created_at":"2026-05-18T12:32:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:3Q2Y23IPIM2NYAFS3CFEA5MJAN","target":"record","payload":{"canonical_record":{"source":{"id":"1803.08636","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-23T02:04:47Z","cross_cats_sorted":["cs.AI","cs.MM"],"title_canon_sha256":"a14a525148744aed511608b8732de0ec15fbdc68dc0f58f12ebad57a2460e4b0","abstract_canon_sha256":"00d4af9e4f600ab65384d82c123e49941970121af2119d4e59e001f77b03570c"},"schema_version":"1.0"},"canonical_sha256":"dc358d6d0f4334dc00b2d88a40758903572490cfab8a3a66d0b4e6c1a8f33e98","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:29.364359Z","signature_b64":"1qv0kHeEGd/4oyt5tlf04YgJUwPhw/MGMKjWq68ADAxdibK/kJ6o/9KWtmlYEU7BuFFZYSJ1e7IhmzTvMlV+AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dc358d6d0f4334dc00b2d88a40758903572490cfab8a3a66d0b4e6c1a8f33e98","last_reissued_at":"2026-05-18T00:03:29.363762Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:29.363762Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.08636","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":"2026-05-18T00:03:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eWwM78f0/LOKRZUIJPfduLMmH5gAs/tdw7GArbeCKJ2loY0RpFlzZ2nDMwOgy6dFnqWLEPrz/DljsTjoRHvKDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T11:10:32.280157Z"},"content_sha256":"f32167c8be3e364aaba76950d38d02f742ee9706f5064c0106e1f224e7836f54","schema_version":"1.0","event_id":"sha256:f32167c8be3e364aaba76950d38d02f742ee9706f5064c0106e1f224e7836f54"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:3Q2Y23IPIM2NYAFS3CFEA5MJAN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PDNet: Prior-model Guided Depth-enhanced Network for Salient Object Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.MM"],"primary_cat":"cs.CV","authors_text":"Chunbiao Zhu, Ge Li, Kan Huang, Thomas H Li, Xing Cai","submitted_at":"2018-03-23T02:04:47Z","abstract_excerpt":"Fully convolutional neural networks (FCNs) have shown outstanding performance in many computer vision tasks including salient object detection. However, there still remains two issues needed to be addressed in deep learning based saliency detection. One is the lack of tremendous amount of annotated data to train a network. The other is the lack of robustness for extracting salient objects in images containing complex scenes. In this paper, we present a new architecture$ - $PDNet, a robust prior-model guided depth-enhanced network for RGB-D salient object detection. In contrast to existing work"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.08636","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":""},"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":"2026-05-18T00:03:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VLaXr59u6CbLY3qbvi+SZ2nOgthkKvSaX6BcR/m7KgqAYyYjyyzJnsJrKxOetu3dnikFa1vCoysx7GmXpUKjDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T11:10:32.280638Z"},"content_sha256":"93205d92ef6da2484662284878aef678c9201b14b58cc7fff96ea101e6b09c60","schema_version":"1.0","event_id":"sha256:93205d92ef6da2484662284878aef678c9201b14b58cc7fff96ea101e6b09c60"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3Q2Y23IPIM2NYAFS3CFEA5MJAN/bundle.json","state_url":"https://pith.science/pith/3Q2Y23IPIM2NYAFS3CFEA5MJAN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3Q2Y23IPIM2NYAFS3CFEA5MJAN/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":"2026-05-25T11:10:32Z","links":{"resolver":"https://pith.science/pith/3Q2Y23IPIM2NYAFS3CFEA5MJAN","bundle":"https://pith.science/pith/3Q2Y23IPIM2NYAFS3CFEA5MJAN/bundle.json","state":"https://pith.science/pith/3Q2Y23IPIM2NYAFS3CFEA5MJAN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3Q2Y23IPIM2NYAFS3CFEA5MJAN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:3Q2Y23IPIM2NYAFS3CFEA5MJAN","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":"00d4af9e4f600ab65384d82c123e49941970121af2119d4e59e001f77b03570c","cross_cats_sorted":["cs.AI","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-23T02:04:47Z","title_canon_sha256":"a14a525148744aed511608b8732de0ec15fbdc68dc0f58f12ebad57a2460e4b0"},"schema_version":"1.0","source":{"id":"1803.08636","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.08636","created_at":"2026-05-18T00:03:29Z"},{"alias_kind":"arxiv_version","alias_value":"1803.08636v2","created_at":"2026-05-18T00:03:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.08636","created_at":"2026-05-18T00:03:29Z"},{"alias_kind":"pith_short_12","alias_value":"3Q2Y23IPIM2N","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"3Q2Y23IPIM2NYAFS","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"3Q2Y23IP","created_at":"2026-05-18T12:32:02Z"}],"graph_snapshots":[{"event_id":"sha256:93205d92ef6da2484662284878aef678c9201b14b58cc7fff96ea101e6b09c60","target":"graph","created_at":"2026-05-18T00:03:29Z","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"},"paper":{"abstract_excerpt":"Fully convolutional neural networks (FCNs) have shown outstanding performance in many computer vision tasks including salient object detection. However, there still remains two issues needed to be addressed in deep learning based saliency detection. One is the lack of tremendous amount of annotated data to train a network. The other is the lack of robustness for extracting salient objects in images containing complex scenes. In this paper, we present a new architecture$ - $PDNet, a robust prior-model guided depth-enhanced network for RGB-D salient object detection. In contrast to existing work","authors_text":"Chunbiao Zhu, Ge Li, Kan Huang, Thomas H Li, Xing Cai","cross_cats":["cs.AI","cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-23T02:04:47Z","title":"PDNet: Prior-model Guided Depth-enhanced Network for Salient Object Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.08636","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:f32167c8be3e364aaba76950d38d02f742ee9706f5064c0106e1f224e7836f54","target":"record","created_at":"2026-05-18T00:03:29Z","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":"00d4af9e4f600ab65384d82c123e49941970121af2119d4e59e001f77b03570c","cross_cats_sorted":["cs.AI","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-23T02:04:47Z","title_canon_sha256":"a14a525148744aed511608b8732de0ec15fbdc68dc0f58f12ebad57a2460e4b0"},"schema_version":"1.0","source":{"id":"1803.08636","kind":"arxiv","version":2}},"canonical_sha256":"dc358d6d0f4334dc00b2d88a40758903572490cfab8a3a66d0b4e6c1a8f33e98","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dc358d6d0f4334dc00b2d88a40758903572490cfab8a3a66d0b4e6c1a8f33e98","first_computed_at":"2026-05-18T00:03:29.363762Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:03:29.363762Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1qv0kHeEGd/4oyt5tlf04YgJUwPhw/MGMKjWq68ADAxdibK/kJ6o/9KWtmlYEU7BuFFZYSJ1e7IhmzTvMlV+AQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:03:29.364359Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.08636","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f32167c8be3e364aaba76950d38d02f742ee9706f5064c0106e1f224e7836f54","sha256:93205d92ef6da2484662284878aef678c9201b14b58cc7fff96ea101e6b09c60"],"state_sha256":"68010322ac40bc2ac3849f6c1028eec87567373a99a30b53b9f701a0d45091c8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nq2zTnTF4HOwjGmI22V8kW95ROrewEA0XwACllXp8yfLQPZQXS9rF5pGxnLV+afCEsJT5bSX8xyE8BnCa4rkAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T11:10:32.283869Z","bundle_sha256":"2c0675f25d5060091200c718de8098f3791fcb1d60eea302ede025f05ca36755"}}