{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:PWTAGCL6EP2FXSM3KFBXFGO6SX","short_pith_number":"pith:PWTAGCL6","canonical_record":{"source":{"id":"1903.01192","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2019-03-04T11:56:53Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"4f4a30dbc2595eadbaccedcbc49cde22b20b9a2bc128355cfd0b8c318d6b8936","abstract_canon_sha256":"d3fab8591cba0b25cbc7a70fb524391103ee6f13ff2ec9963ca037b2ebdd308c"},"schema_version":"1.0"},"canonical_sha256":"7da603097e23f45bc99b51437299de95dc825e44c4679960a935d90bb69f16f8","source":{"kind":"arxiv","id":"1903.01192","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.01192","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"arxiv_version","alias_value":"1903.01192v4","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.01192","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"pith_short_12","alias_value":"PWTAGCL6EP2F","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"pith_short_16","alias_value":"PWTAGCL6EP2FXSM3","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"pith_short_8","alias_value":"PWTAGCL6","created_at":"2026-07-05T10:16:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:PWTAGCL6EP2FXSM3KFBXFGO6SX","target":"record","payload":{"canonical_record":{"source":{"id":"1903.01192","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2019-03-04T11:56:53Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"4f4a30dbc2595eadbaccedcbc49cde22b20b9a2bc128355cfd0b8c318d6b8936","abstract_canon_sha256":"d3fab8591cba0b25cbc7a70fb524391103ee6f13ff2ec9963ca037b2ebdd308c"},"schema_version":"1.0"},"canonical_sha256":"7da603097e23f45bc99b51437299de95dc825e44c4679960a935d90bb69f16f8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:16:04.101330Z","signature_b64":"CKjZEnd5g7uOMlKRF5GMjujVdnEtiQBgjArOFeRtkOmBohdY918wC5TJoa3h1GcnLlkUDMhDfiocgOraqw0HBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7da603097e23f45bc99b51437299de95dc825e44c4679960a935d90bb69f16f8","last_reissued_at":"2026-07-05T10:16:04.100794Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:16:04.100794Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.01192","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:16:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SgzyW/peYeMyatrYZV7A0SuNXQvhAaY98eefagXGxRTCBF/BpbrD/LpYxJX0pLa8U4n3FRGhrTejsxprb+JaDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T19:53:07.961434Z"},"content_sha256":"e5eb6285c73a9c6c7cdc7c9c952eea2fac514f6222a9547cdaa712b7ee396c3f","schema_version":"1.0","event_id":"sha256:e5eb6285c73a9c6c7cdc7c9c952eea2fac514f6222a9547cdaa712b7ee396c3f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:PWTAGCL6EP2FXSM3KFBXFGO6SX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"STEFANN: Scene Text Editor using Font Adaptive Neural Network","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CV","authors_text":"Prasun Roy, Saumik Bhattacharya, Subhankar Ghosh, Umapada Pal","submitted_at":"2019-03-04T11:56:53Z","abstract_excerpt":"Textual information in a captured scene plays an important role in scene interpretation and decision making. Though there exist methods that can successfully detect and interpret complex text regions present in a scene, to the best of our knowledge, there is no significant prior work that aims to modify the textual information in an image. The ability to edit text directly on images has several advantages including error correction, text restoration and image reusability. In this paper, we propose a method to modify text in an image at character-level. We approach the problem in two stages. At"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.01192","kind":"arxiv","version":4},"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/1903.01192/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":"2026-07-05T10:16:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FG7DfAQ5IoQrt/e9SsZSSRiyuXPchLdRdi8h0etYnH7U3I+oWszPyvwMQZNXXAvZMh3tLne4bh+6ebC74eQuCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T19:53:07.962444Z"},"content_sha256":"a95e6035f5e61b5864a50f6902fff3ba509fb6cdef45edccdcccbf7d0473d3b8","schema_version":"1.0","event_id":"sha256:a95e6035f5e61b5864a50f6902fff3ba509fb6cdef45edccdcccbf7d0473d3b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PWTAGCL6EP2FXSM3KFBXFGO6SX/bundle.json","state_url":"https://pith.science/pith/PWTAGCL6EP2FXSM3KFBXFGO6SX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PWTAGCL6EP2FXSM3KFBXFGO6SX/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":"2026-08-15T19:53:07Z","links":{"resolver":"https://pith.science/pith/PWTAGCL6EP2FXSM3KFBXFGO6SX","bundle":"https://pith.science/pith/PWTAGCL6EP2FXSM3KFBXFGO6SX/bundle.json","state":"https://pith.science/pith/PWTAGCL6EP2FXSM3KFBXFGO6SX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PWTAGCL6EP2FXSM3KFBXFGO6SX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:PWTAGCL6EP2FXSM3KFBXFGO6SX","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":"d3fab8591cba0b25cbc7a70fb524391103ee6f13ff2ec9963ca037b2ebdd308c","cross_cats_sorted":["cs.MM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2019-03-04T11:56:53Z","title_canon_sha256":"4f4a30dbc2595eadbaccedcbc49cde22b20b9a2bc128355cfd0b8c318d6b8936"},"schema_version":"1.0","source":{"id":"1903.01192","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.01192","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"arxiv_version","alias_value":"1903.01192v4","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.01192","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"pith_short_12","alias_value":"PWTAGCL6EP2F","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"pith_short_16","alias_value":"PWTAGCL6EP2FXSM3","created_at":"2026-07-05T10:16:04Z"},{"alias_kind":"pith_short_8","alias_value":"PWTAGCL6","created_at":"2026-07-05T10:16:04Z"}],"graph_snapshots":[{"event_id":"sha256:a95e6035f5e61b5864a50f6902fff3ba509fb6cdef45edccdcccbf7d0473d3b8","target":"graph","created_at":"2026-07-05T10:16:04Z","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/1903.01192/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Textual information in a captured scene plays an important role in scene interpretation and decision making. Though there exist methods that can successfully detect and interpret complex text regions present in a scene, to the best of our knowledge, there is no significant prior work that aims to modify the textual information in an image. The ability to edit text directly on images has several advantages including error correction, text restoration and image reusability. In this paper, we propose a method to modify text in an image at character-level. We approach the problem in two stages. At","authors_text":"Prasun Roy, Saumik Bhattacharya, Subhankar Ghosh, Umapada Pal","cross_cats":["cs.MM"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2019-03-04T11:56:53Z","title":"STEFANN: Scene Text Editor using Font Adaptive Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.01192","kind":"arxiv","version":4},"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:e5eb6285c73a9c6c7cdc7c9c952eea2fac514f6222a9547cdaa712b7ee396c3f","target":"record","created_at":"2026-07-05T10:16:04Z","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":"d3fab8591cba0b25cbc7a70fb524391103ee6f13ff2ec9963ca037b2ebdd308c","cross_cats_sorted":["cs.MM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2019-03-04T11:56:53Z","title_canon_sha256":"4f4a30dbc2595eadbaccedcbc49cde22b20b9a2bc128355cfd0b8c318d6b8936"},"schema_version":"1.0","source":{"id":"1903.01192","kind":"arxiv","version":4}},"canonical_sha256":"7da603097e23f45bc99b51437299de95dc825e44c4679960a935d90bb69f16f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7da603097e23f45bc99b51437299de95dc825e44c4679960a935d90bb69f16f8","first_computed_at":"2026-07-05T10:16:04.100794Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:16:04.100794Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CKjZEnd5g7uOMlKRF5GMjujVdnEtiQBgjArOFeRtkOmBohdY918wC5TJoa3h1GcnLlkUDMhDfiocgOraqw0HBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:16:04.101330Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.01192","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e5eb6285c73a9c6c7cdc7c9c952eea2fac514f6222a9547cdaa712b7ee396c3f","sha256:a95e6035f5e61b5864a50f6902fff3ba509fb6cdef45edccdcccbf7d0473d3b8"],"state_sha256":"e2708af811ecf46af8ddcae6061b13d6743df42e25f34ffb98fb0944f2942097"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FBuRiF9b4nVspAbiaokcFyQ0wIvsktJDhV9gmutQzQwv8oqEOJ79oQy6mgOpAO3CIzT1Duir6Y+Mtgmn8YUMDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T19:53:07.969817Z","bundle_sha256":"cd82715ff02583610036f4bf01feadcce0bee8d87c5bbc98b1a8bc7e7cbed6c1"}}