{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:EBF7C3GMIOM4ZHFCUALYKNQSLI","short_pith_number":"pith:EBF7C3GM","canonical_record":{"source":{"id":"2207.05921","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-07-13T02:01:07Z","cross_cats_sorted":[],"title_canon_sha256":"2482cf07462912da454da4544694df946387462e45a5cc61d6d5ea6ec241522e","abstract_canon_sha256":"aa522e379b1e84b64fb94f9ccac821cb0403ba4677de28b12be15df8c0ac3c6e"},"schema_version":"1.0"},"canonical_sha256":"204bf16ccc4399cc9ca2a0178536125a1f0c1703a9bc0c90bb4f2128ce82cdc3","source":{"kind":"arxiv","id":"2207.05921","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.05921","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"arxiv_version","alias_value":"2207.05921v3","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.05921","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"pith_short_12","alias_value":"EBF7C3GMIOM4","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"pith_short_16","alias_value":"EBF7C3GMIOM4ZHFC","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"pith_short_8","alias_value":"EBF7C3GM","created_at":"2026-07-05T06:08:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:EBF7C3GMIOM4ZHFCUALYKNQSLI","target":"record","payload":{"canonical_record":{"source":{"id":"2207.05921","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-07-13T02:01:07Z","cross_cats_sorted":[],"title_canon_sha256":"2482cf07462912da454da4544694df946387462e45a5cc61d6d5ea6ec241522e","abstract_canon_sha256":"aa522e379b1e84b64fb94f9ccac821cb0403ba4677de28b12be15df8c0ac3c6e"},"schema_version":"1.0"},"canonical_sha256":"204bf16ccc4399cc9ca2a0178536125a1f0c1703a9bc0c90bb4f2128ce82cdc3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:08:06.186568Z","signature_b64":"9yPvfOK5obxTYht8Nyl2a5yg/ExKL8Csr+p8e3tcDbm4qZ7VwnXS2YskUcsJEsThZdYcPJ1V9Lkz0lgJTUq8Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"204bf16ccc4399cc9ca2a0178536125a1f0c1703a9bc0c90bb4f2128ce82cdc3","last_reissued_at":"2026-07-05T06:08:06.186109Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:08:06.186109Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.05921","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:08:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"piqTOSiORlhmADTrgSkei0pRqMjfe9RaTHXgVlMGU/+WpqL+csLRFg0fFLBgD1I2JGFTFN9BNCiFeKIN1aNkAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T22:10:51.721025Z"},"content_sha256":"29bc2515d9880aadd85b66d22771c052e7c4111ad9b8efd8d2718f63435b5980","schema_version":"1.0","event_id":"sha256:29bc2515d9880aadd85b66d22771c052e7c4111ad9b8efd8d2718f63435b5980"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:EBF7C3GMIOM4ZHFCUALYKNQSLI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Texture-guided Saliency Distilling for Unsupervised Salient Object Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bo Qiao, Huajun Zhou, Jianhuang Lai, Lingxiao Yang, Xiaohua Xie","submitted_at":"2022-07-13T02:01:07Z","abstract_excerpt":"Deep Learning-based Unsupervised Salient Object Detection (USOD) mainly relies on the noisy saliency pseudo labels that have been generated from traditional handcraft methods or pre-trained networks. To cope with the noisy labels problem, a class of methods focus on only easy samples with reliable labels but ignore valuable knowledge in hard samples. In this paper, we propose a novel USOD method to mine rich and accurate saliency knowledge from both easy and hard samples. First, we propose a Confidence-aware Saliency Distilling (CSD) strategy that scores samples conditioned on samples' confide"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.05921","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2207.05921/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":"2026-07-05T06:08:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9SuaNz3oxRpmN8Kf9U7lxDnT1TmCRCv9zvvRxtlxg0//QNKIB3oBHzlVM9hkFF4UeOTU3ahXqGwhKQvHlvsFCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T22:10:51.721546Z"},"content_sha256":"059c596e0767b82a58cc960bafbbad41d243218b4245448aa1f3c4746c2f6741","schema_version":"1.0","event_id":"sha256:059c596e0767b82a58cc960bafbbad41d243218b4245448aa1f3c4746c2f6741"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EBF7C3GMIOM4ZHFCUALYKNQSLI/bundle.json","state_url":"https://pith.science/pith/EBF7C3GMIOM4ZHFCUALYKNQSLI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EBF7C3GMIOM4ZHFCUALYKNQSLI/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":"2026-07-31T22:10:51Z","links":{"resolver":"https://pith.science/pith/EBF7C3GMIOM4ZHFCUALYKNQSLI","bundle":"https://pith.science/pith/EBF7C3GMIOM4ZHFCUALYKNQSLI/bundle.json","state":"https://pith.science/pith/EBF7C3GMIOM4ZHFCUALYKNQSLI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EBF7C3GMIOM4ZHFCUALYKNQSLI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:EBF7C3GMIOM4ZHFCUALYKNQSLI","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":"aa522e379b1e84b64fb94f9ccac821cb0403ba4677de28b12be15df8c0ac3c6e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-07-13T02:01:07Z","title_canon_sha256":"2482cf07462912da454da4544694df946387462e45a5cc61d6d5ea6ec241522e"},"schema_version":"1.0","source":{"id":"2207.05921","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.05921","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"arxiv_version","alias_value":"2207.05921v3","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.05921","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"pith_short_12","alias_value":"EBF7C3GMIOM4","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"pith_short_16","alias_value":"EBF7C3GMIOM4ZHFC","created_at":"2026-07-05T06:08:06Z"},{"alias_kind":"pith_short_8","alias_value":"EBF7C3GM","created_at":"2026-07-05T06:08:06Z"}],"graph_snapshots":[{"event_id":"sha256:059c596e0767b82a58cc960bafbbad41d243218b4245448aa1f3c4746c2f6741","target":"graph","created_at":"2026-07-05T06:08:06Z","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/2207.05921/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep Learning-based Unsupervised Salient Object Detection (USOD) mainly relies on the noisy saliency pseudo labels that have been generated from traditional handcraft methods or pre-trained networks. To cope with the noisy labels problem, a class of methods focus on only easy samples with reliable labels but ignore valuable knowledge in hard samples. In this paper, we propose a novel USOD method to mine rich and accurate saliency knowledge from both easy and hard samples. First, we propose a Confidence-aware Saliency Distilling (CSD) strategy that scores samples conditioned on samples' confide","authors_text":"Bo Qiao, Huajun Zhou, Jianhuang Lai, Lingxiao Yang, Xiaohua Xie","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-07-13T02:01:07Z","title":"Texture-guided Saliency Distilling for Unsupervised Salient Object Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.05921","kind":"arxiv","version":3},"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":"sha256:29bc2515d9880aadd85b66d22771c052e7c4111ad9b8efd8d2718f63435b5980","target":"record","created_at":"2026-07-05T06:08:06Z","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":"aa522e379b1e84b64fb94f9ccac821cb0403ba4677de28b12be15df8c0ac3c6e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-07-13T02:01:07Z","title_canon_sha256":"2482cf07462912da454da4544694df946387462e45a5cc61d6d5ea6ec241522e"},"schema_version":"1.0","source":{"id":"2207.05921","kind":"arxiv","version":3}},"canonical_sha256":"204bf16ccc4399cc9ca2a0178536125a1f0c1703a9bc0c90bb4f2128ce82cdc3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"204bf16ccc4399cc9ca2a0178536125a1f0c1703a9bc0c90bb4f2128ce82cdc3","first_computed_at":"2026-07-05T06:08:06.186109Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:08:06.186109Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9yPvfOK5obxTYht8Nyl2a5yg/ExKL8Csr+p8e3tcDbm4qZ7VwnXS2YskUcsJEsThZdYcPJ1V9Lkz0lgJTUq8Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T06:08:06.186568Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.05921","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:29bc2515d9880aadd85b66d22771c052e7c4111ad9b8efd8d2718f63435b5980","sha256:059c596e0767b82a58cc960bafbbad41d243218b4245448aa1f3c4746c2f6741"],"state_sha256":"dd3303e58639185ed3ddd406f42f9eba6a9a17d3c058bc149ecd034e5f27e317"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i+Mj+zUytS2qmRp1MDleSQ86CnCum9LKVZsExFJNQ1Ue/HQ/h4jzcfnmyJvMrzsvjxfiO0sPlt/E5Rdm6U36Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T22:10:51.725428Z","bundle_sha256":"fc1ef90999d05c360b08ccbc0f7865b4df617ab463233e055b7ec7329455b1a3"}}