{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:VVVU7STU6QKTY22ENGJAEKUYX2","short_pith_number":"pith:VVVU7STU","schema_version":"1.0","canonical_sha256":"ad6b4fca74f4153c6b446992022a98be928a49d3d3ffdcc89336c2cf01123073","source":{"kind":"arxiv","id":"2409.12421","version":1},"attestation_state":"computed","paper":{"title":"Frequency-Guided Spatial Adaptation for Camouflaged Object Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dexuan Kong, Guoqiang Liang, Hexu Wang, Lingyan Ran, Shizhou Zhang, Yanning Zhang, Yinghui Xing, Yue Lu","submitted_at":"2024-09-19T02:53:48Z","abstract_excerpt":"Camouflaged object detection (COD) aims to segment camouflaged objects which exhibit very similar patterns with the surrounding environment. Recent research works have shown that enhancing the feature representation via the frequency information can greatly alleviate the ambiguity problem between the foreground objects and the background.With the emergence of vision foundation models, like InternImage, Segment Anything Model etc, adapting the pretrained model on COD tasks with a lightweight adapter module shows a novel and promising research direction. Existing adapter modules mainly care abou"},"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":"2409.12421","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-19T02:53:48Z","cross_cats_sorted":[],"title_canon_sha256":"408449525ed02294199a711bb1c0bab53626312688e06b1ab1b51aefbe0f278c","abstract_canon_sha256":"3a95709c62c53b4cfacdbb0fc1090997003e25993f8785f8c856e2f9e7aad2de"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:08:53.831299Z","signature_b64":"KpCcomSnYkHjLe7SqDxy9VrEV5uoiwHnpmJe9ktIrtjuE5zhTpsV1JaNF+TtBLtHaA3rtWLcGBo7bi0d0oHWCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ad6b4fca74f4153c6b446992022a98be928a49d3d3ffdcc89336c2cf01123073","last_reissued_at":"2026-07-05T09:08:53.830794Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:08:53.830794Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Frequency-Guided Spatial Adaptation for Camouflaged Object Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dexuan Kong, Guoqiang Liang, Hexu Wang, Lingyan Ran, Shizhou Zhang, Yanning Zhang, Yinghui Xing, Yue Lu","submitted_at":"2024-09-19T02:53:48Z","abstract_excerpt":"Camouflaged object detection (COD) aims to segment camouflaged objects which exhibit very similar patterns with the surrounding environment. Recent research works have shown that enhancing the feature representation via the frequency information can greatly alleviate the ambiguity problem between the foreground objects and the background.With the emergence of vision foundation models, like InternImage, Segment Anything Model etc, adapting the pretrained model on COD tasks with a lightweight adapter module shows a novel and promising research direction. Existing adapter modules mainly care abou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.12421","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/2409.12421/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2409.12421","created_at":"2026-07-05T09:08:53.830864+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.12421v1","created_at":"2026-07-05T09:08:53.830864+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.12421","created_at":"2026-07-05T09:08:53.830864+00:00"},{"alias_kind":"pith_short_12","alias_value":"VVVU7STU6QKT","created_at":"2026-07-05T09:08:53.830864+00:00"},{"alias_kind":"pith_short_16","alias_value":"VVVU7STU6QKTY22E","created_at":"2026-07-05T09:08:53.830864+00:00"},{"alias_kind":"pith_short_8","alias_value":"VVVU7STU","created_at":"2026-07-05T09:08:53.830864+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/VVVU7STU6QKTY22ENGJAEKUYX2","json":"https://pith.science/pith/VVVU7STU6QKTY22ENGJAEKUYX2.json","graph_json":"https://pith.science/api/pith-number/VVVU7STU6QKTY22ENGJAEKUYX2/graph.json","events_json":"https://pith.science/api/pith-number/VVVU7STU6QKTY22ENGJAEKUYX2/events.json","paper":"https://pith.science/paper/VVVU7STU"},"agent_actions":{"view_html":"https://pith.science/pith/VVVU7STU6QKTY22ENGJAEKUYX2","download_json":"https://pith.science/pith/VVVU7STU6QKTY22ENGJAEKUYX2.json","view_paper":"https://pith.science/paper/VVVU7STU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.12421&json=true","fetch_graph":"https://pith.science/api/pith-number/VVVU7STU6QKTY22ENGJAEKUYX2/graph.json","fetch_events":"https://pith.science/api/pith-number/VVVU7STU6QKTY22ENGJAEKUYX2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VVVU7STU6QKTY22ENGJAEKUYX2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VVVU7STU6QKTY22ENGJAEKUYX2/action/storage_attestation","attest_author":"https://pith.science/pith/VVVU7STU6QKTY22ENGJAEKUYX2/action/author_attestation","sign_citation":"https://pith.science/pith/VVVU7STU6QKTY22ENGJAEKUYX2/action/citation_signature","submit_replication":"https://pith.science/pith/VVVU7STU6QKTY22ENGJAEKUYX2/action/replication_record"}},"created_at":"2026-07-05T09:08:53.830864+00:00","updated_at":"2026-07-05T09:08:53.830864+00:00"}