{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:JACUI2447YDK35AGQ4SSTXKMPG","short_pith_number":"pith:JACUI244","schema_version":"1.0","canonical_sha256":"4805446b9cfe06adf406872529dd4c799ce68cdceeb3cbe8bccdadd84ad197e1","source":{"kind":"arxiv","id":"2402.17624","version":1},"attestation_state":"computed","paper":{"title":"CustomSketching: Sketch Concept Extraction for Sketch-based Image Synthesis and Editing","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Chufeng Xiao, Hongbo Fu","submitted_at":"2024-02-27T15:52:59Z","abstract_excerpt":"Personalization techniques for large text-to-image (T2I) models allow users to incorporate new concepts from reference images. However, existing methods primarily rely on textual descriptions, leading to limited control over customized images and failing to support fine-grained and local editing (e.g., shape, pose, and details). In this paper, we identify sketches as an intuitive and versatile representation that can facilitate such control, e.g., contour lines capturing shape information and flow lines representing texture. This motivates us to explore a novel task of sketch concept extractio"},"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":"2402.17624","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-02-27T15:52:59Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"ff357a20aca9c09990774edaa9b9a40e7183a699525dd7b69e5b9266b9b14bf4","abstract_canon_sha256":"81819c735565684eea7074bd8cefed9620ee7322b1da993196acbcb8c921c8d9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:49:49.164302Z","signature_b64":"3CoMvbBNLvCJVccBD5e+ngBZ2yo5RrxzQTfc9V8ZjEAwoAVTUF29R7eaoPRvYhHPSn7TACGmki7BvASszFm0Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4805446b9cfe06adf406872529dd4c799ce68cdceeb3cbe8bccdadd84ad197e1","last_reissued_at":"2026-07-05T07:49:49.163965Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:49:49.163965Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CustomSketching: Sketch Concept Extraction for Sketch-based Image Synthesis and Editing","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Chufeng Xiao, Hongbo Fu","submitted_at":"2024-02-27T15:52:59Z","abstract_excerpt":"Personalization techniques for large text-to-image (T2I) models allow users to incorporate new concepts from reference images. However, existing methods primarily rely on textual descriptions, leading to limited control over customized images and failing to support fine-grained and local editing (e.g., shape, pose, and details). In this paper, we identify sketches as an intuitive and versatile representation that can facilitate such control, e.g., contour lines capturing shape information and flow lines representing texture. This motivates us to explore a novel task of sketch concept extractio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.17624","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/2402.17624/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":"2402.17624","created_at":"2026-07-05T07:49:49.164022+00:00"},{"alias_kind":"arxiv_version","alias_value":"2402.17624v1","created_at":"2026-07-05T07:49:49.164022+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.17624","created_at":"2026-07-05T07:49:49.164022+00:00"},{"alias_kind":"pith_short_12","alias_value":"JACUI2447YDK","created_at":"2026-07-05T07:49:49.164022+00:00"},{"alias_kind":"pith_short_16","alias_value":"JACUI2447YDK35AG","created_at":"2026-07-05T07:49:49.164022+00:00"},{"alias_kind":"pith_short_8","alias_value":"JACUI244","created_at":"2026-07-05T07:49:49.164022+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2411.09703","citing_title":"MagicQuill: An Intelligent Interactive Image Editing System","ref_index":71,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JACUI2447YDK35AGQ4SSTXKMPG","json":"https://pith.science/pith/JACUI2447YDK35AGQ4SSTXKMPG.json","graph_json":"https://pith.science/api/pith-number/JACUI2447YDK35AGQ4SSTXKMPG/graph.json","events_json":"https://pith.science/api/pith-number/JACUI2447YDK35AGQ4SSTXKMPG/events.json","paper":"https://pith.science/paper/JACUI244"},"agent_actions":{"view_html":"https://pith.science/pith/JACUI2447YDK35AGQ4SSTXKMPG","download_json":"https://pith.science/pith/JACUI2447YDK35AGQ4SSTXKMPG.json","view_paper":"https://pith.science/paper/JACUI244","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2402.17624&json=true","fetch_graph":"https://pith.science/api/pith-number/JACUI2447YDK35AGQ4SSTXKMPG/graph.json","fetch_events":"https://pith.science/api/pith-number/JACUI2447YDK35AGQ4SSTXKMPG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JACUI2447YDK35AGQ4SSTXKMPG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JACUI2447YDK35AGQ4SSTXKMPG/action/storage_attestation","attest_author":"https://pith.science/pith/JACUI2447YDK35AGQ4SSTXKMPG/action/author_attestation","sign_citation":"https://pith.science/pith/JACUI2447YDK35AGQ4SSTXKMPG/action/citation_signature","submit_replication":"https://pith.science/pith/JACUI2447YDK35AGQ4SSTXKMPG/action/replication_record"}},"created_at":"2026-07-05T07:49:49.164022+00:00","updated_at":"2026-07-05T07:49:49.164022+00:00"}