{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:RODUP6WHYZDCZ5XGLYMT4ZRO3L","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":"8497da12f49bbc8ed1039cdb5ae0df5f783796521a59c27b8b34a03b6c7a769b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-05-25T15:25:18Z","title_canon_sha256":"e67f97cc6d703737e57bbca83d3b64bc6fdbeb638eec34a66c90f756ee0271d4"},"schema_version":"1.0","source":{"id":"2205.12853","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.12853","created_at":"2026-07-05T06:17:25Z"},{"alias_kind":"arxiv_version","alias_value":"2205.12853v2","created_at":"2026-07-05T06:17:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.12853","created_at":"2026-07-05T06:17:25Z"},{"alias_kind":"pith_short_12","alias_value":"RODUP6WHYZDC","created_at":"2026-07-05T06:17:25Z"},{"alias_kind":"pith_short_16","alias_value":"RODUP6WHYZDCZ5XG","created_at":"2026-07-05T06:17:25Z"},{"alias_kind":"pith_short_8","alias_value":"RODUP6WH","created_at":"2026-07-05T06:17:25Z"}],"graph_snapshots":[{"event_id":"sha256:18a1c15e05d9db9433ffcfbebae77eb4d21432eda25eaf74bae087bf12ac5470","target":"graph","created_at":"2026-07-05T06:17:25Z","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/2205.12853/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces DGNet, a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD). It decouples the task into two connected branches, i.e., a context and a texture encoder. The essential connection is the gradient-induced transition, representing a soft grouping between context and texture features. Benefiting from the simple but efficient framework, DGNet outperforms existing state-of-the-art COD models by a large margin. Notably, our efficient version, DGNet-S, runs in real-time (80 fps) and achieves comparable results to the cutting-edge mo","authors_text":"Alexander Liniger, Deng-Ping Fan, Dengxin Dai, Ge-Peng Ji, Luc Van Gool, Yu-Cheng Chou","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-05-25T15:25:18Z","title":"Deep Gradient Learning for Efficient Camouflaged Object Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.12853","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":"sha256:6afab217070bb0bce1e279c7874947d2091f7cff62209d6c28465ead168bcfcb","target":"record","created_at":"2026-07-05T06:17:25Z","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":"8497da12f49bbc8ed1039cdb5ae0df5f783796521a59c27b8b34a03b6c7a769b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-05-25T15:25:18Z","title_canon_sha256":"e67f97cc6d703737e57bbca83d3b64bc6fdbeb638eec34a66c90f756ee0271d4"},"schema_version":"1.0","source":{"id":"2205.12853","kind":"arxiv","version":2}},"canonical_sha256":"8b8747fac7c6462cf6e65e193e662edadea7de167c68a09a223975111a182767","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8b8747fac7c6462cf6e65e193e662edadea7de167c68a09a223975111a182767","first_computed_at":"2026-07-05T06:17:25.625503Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:17:25.625503Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"54z846X0/9tsn96zmoW6/ZZsKW5zMYX9WeE2D2uL29eXz+SFCZ9BIGvQdq7cwLZ9QLeImSz0T70UcKVmf/qpDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:17:25.626026Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.12853","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6afab217070bb0bce1e279c7874947d2091f7cff62209d6c28465ead168bcfcb","sha256:18a1c15e05d9db9433ffcfbebae77eb4d21432eda25eaf74bae087bf12ac5470"],"state_sha256":"946cdc101592c09e33ce970da00a427121776b40ba141ba935d29e809f527a41"}