{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:5NCWFOLXJHS4GVRCHE7Q6QCFXP","short_pith_number":"pith:5NCWFOLX","canonical_record":{"source":{"id":"2303.09801","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-17T07:07:17Z","cross_cats_sorted":[],"title_canon_sha256":"ff20df6f67232cfc0ffd2f7400354b7f0f2ce9cc5a3a55d11bc185671093a550","abstract_canon_sha256":"2087551596404f2a247d296d3744e3732ec744487ea5dbf0c64ab430b918a232"},"schema_version":"1.0"},"canonical_sha256":"eb4562b97749e5c35622393f0f4045bbfd3d421b477467038121dd21d8eb2646","source":{"kind":"arxiv","id":"2303.09801","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.09801","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"arxiv_version","alias_value":"2303.09801v1","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.09801","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"pith_short_12","alias_value":"5NCWFOLXJHS4","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"pith_short_16","alias_value":"5NCWFOLXJHS4GVRC","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"pith_short_8","alias_value":"5NCWFOLX","created_at":"2026-07-05T05:52:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:5NCWFOLXJHS4GVRCHE7Q6QCFXP","target":"record","payload":{"canonical_record":{"source":{"id":"2303.09801","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-17T07:07:17Z","cross_cats_sorted":[],"title_canon_sha256":"ff20df6f67232cfc0ffd2f7400354b7f0f2ce9cc5a3a55d11bc185671093a550","abstract_canon_sha256":"2087551596404f2a247d296d3744e3732ec744487ea5dbf0c64ab430b918a232"},"schema_version":"1.0"},"canonical_sha256":"eb4562b97749e5c35622393f0f4045bbfd3d421b477467038121dd21d8eb2646","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:52:10.935692Z","signature_b64":"dFeMc59Pu4TSvLUWVCkfiIBU4bPv3p8lqz+P0R6UiE9hXNXN2xWsUta19B6vJrzVKnEP+s1Q1ncmGlVtzRZnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eb4562b97749e5c35622393f0f4045bbfd3d421b477467038121dd21d8eb2646","last_reissued_at":"2026-07-05T05:52:10.935154Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:52:10.935154Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.09801","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:52:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7aqqVCLRNyL7rwZS+SBLstX1U+XG3NYOckqzT9D9znfmNaG38/Vf2uIemnjxMjIlR5vvZhy5xes3bHXDuZoWAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:34:27.288611Z"},"content_sha256":"bb383adbd81bc04c6bdcc6eb6bb43dbc17f5a1f3003424b649bc97d20fda71ca","schema_version":"1.0","event_id":"sha256:bb383adbd81bc04c6bdcc6eb6bb43dbc17f5a1f3003424b649bc97d20fda71ca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:5NCWFOLXJHS4GVRCHE7Q6QCFXP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptive Graph Convolution Module for Salient Object Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Minhyeok Lee, Sangyoun Lee, Suhwan Cho, Yongwoo Lee","submitted_at":"2023-03-17T07:07:17Z","abstract_excerpt":"Salient object detection (SOD) is a task that involves identifying and segmenting the most visually prominent object in an image. Existing solutions can accomplish this use a multi-scale feature fusion mechanism to detect the global context of an image. However, as there is no consideration of the structures in the image nor the relations between distant pixels, conventional methods cannot deal with complex scenes effectively. In this paper, we propose an adaptive graph convolution module (AGCM) to overcome these limitations. Prototype features are initially extracted from the input image usin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.09801","kind":"arxiv","version":1},"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/2303.09801/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":"2026-07-05T05:52:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9Xo2H1z8Fp06ddM++zPNz3VYWlfwIkeki0YhsIJxG1z2ZELzyM+YFc/NECoDEr4oEajtRIZi9iiSPdlka2wRBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:34:27.289583Z"},"content_sha256":"5c7bfa7359df96b1abbf51ffb4d0239ecd477425659886151b3095d630671b9a","schema_version":"1.0","event_id":"sha256:5c7bfa7359df96b1abbf51ffb4d0239ecd477425659886151b3095d630671b9a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5NCWFOLXJHS4GVRCHE7Q6QCFXP/bundle.json","state_url":"https://pith.science/pith/5NCWFOLXJHS4GVRCHE7Q6QCFXP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5NCWFOLXJHS4GVRCHE7Q6QCFXP/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":"2026-08-05T18:34:27Z","links":{"resolver":"https://pith.science/pith/5NCWFOLXJHS4GVRCHE7Q6QCFXP","bundle":"https://pith.science/pith/5NCWFOLXJHS4GVRCHE7Q6QCFXP/bundle.json","state":"https://pith.science/pith/5NCWFOLXJHS4GVRCHE7Q6QCFXP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5NCWFOLXJHS4GVRCHE7Q6QCFXP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5NCWFOLXJHS4GVRCHE7Q6QCFXP","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":"2087551596404f2a247d296d3744e3732ec744487ea5dbf0c64ab430b918a232","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-17T07:07:17Z","title_canon_sha256":"ff20df6f67232cfc0ffd2f7400354b7f0f2ce9cc5a3a55d11bc185671093a550"},"schema_version":"1.0","source":{"id":"2303.09801","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.09801","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"arxiv_version","alias_value":"2303.09801v1","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.09801","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"pith_short_12","alias_value":"5NCWFOLXJHS4","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"pith_short_16","alias_value":"5NCWFOLXJHS4GVRC","created_at":"2026-07-05T05:52:10Z"},{"alias_kind":"pith_short_8","alias_value":"5NCWFOLX","created_at":"2026-07-05T05:52:10Z"}],"graph_snapshots":[{"event_id":"sha256:5c7bfa7359df96b1abbf51ffb4d0239ecd477425659886151b3095d630671b9a","target":"graph","created_at":"2026-07-05T05:52:10Z","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/2303.09801/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Salient object detection (SOD) is a task that involves identifying and segmenting the most visually prominent object in an image. Existing solutions can accomplish this use a multi-scale feature fusion mechanism to detect the global context of an image. However, as there is no consideration of the structures in the image nor the relations between distant pixels, conventional methods cannot deal with complex scenes effectively. In this paper, we propose an adaptive graph convolution module (AGCM) to overcome these limitations. Prototype features are initially extracted from the input image usin","authors_text":"Minhyeok Lee, Sangyoun Lee, Suhwan Cho, Yongwoo Lee","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-17T07:07:17Z","title":"Adaptive Graph Convolution Module for Salient Object Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.09801","kind":"arxiv","version":1},"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:bb383adbd81bc04c6bdcc6eb6bb43dbc17f5a1f3003424b649bc97d20fda71ca","target":"record","created_at":"2026-07-05T05:52:10Z","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":"2087551596404f2a247d296d3744e3732ec744487ea5dbf0c64ab430b918a232","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-17T07:07:17Z","title_canon_sha256":"ff20df6f67232cfc0ffd2f7400354b7f0f2ce9cc5a3a55d11bc185671093a550"},"schema_version":"1.0","source":{"id":"2303.09801","kind":"arxiv","version":1}},"canonical_sha256":"eb4562b97749e5c35622393f0f4045bbfd3d421b477467038121dd21d8eb2646","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eb4562b97749e5c35622393f0f4045bbfd3d421b477467038121dd21d8eb2646","first_computed_at":"2026-07-05T05:52:10.935154Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:52:10.935154Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dFeMc59Pu4TSvLUWVCkfiIBU4bPv3p8lqz+P0R6UiE9hXNXN2xWsUta19B6vJrzVKnEP+s1Q1ncmGlVtzRZnAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:52:10.935692Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.09801","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb383adbd81bc04c6bdcc6eb6bb43dbc17f5a1f3003424b649bc97d20fda71ca","sha256:5c7bfa7359df96b1abbf51ffb4d0239ecd477425659886151b3095d630671b9a"],"state_sha256":"1be0791451588a7609cbc87eb1d7796eaaadfd895be8075ed06217018481ff2a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6IzmsenaJZCmzf/lN8ODXBMu8VKCoYZZy2yYoC2yY45OmzAM7kuxXt41pzZk8Hdi07uZE+xWIRU0jde93qBLBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T18:34:27.296084Z","bundle_sha256":"8ef715f2083ca85e7bbc3407a18ff54297d28dbd52c8e7a76c471996e2f442ff"}}