{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:JH6EJDEFF4EZAGMN47U6U26FJI","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":"9ed02d4734286b38c1210ddff406c23a5783be4a1fbb309e3470956ef9da42b5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-01-27T09:41:58Z","title_canon_sha256":"b4cb93b4b5a4e097ea2d17b9b3d2ea750257fca5ed1a4f67716aec4848bca782"},"schema_version":"1.0","source":{"id":"2201.11403","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.11403","created_at":"2026-07-05T04:57:24Z"},{"alias_kind":"arxiv_version","alias_value":"2201.11403v5","created_at":"2026-07-05T04:57:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.11403","created_at":"2026-07-05T04:57:24Z"},{"alias_kind":"pith_short_12","alias_value":"JH6EJDEFF4EZ","created_at":"2026-07-05T04:57:24Z"},{"alias_kind":"pith_short_16","alias_value":"JH6EJDEFF4EZAGMN","created_at":"2026-07-05T04:57:24Z"},{"alias_kind":"pith_short_8","alias_value":"JH6EJDEF","created_at":"2026-07-05T04:57:24Z"}],"graph_snapshots":[{"event_id":"sha256:a41b1f60eb20a3041c5ae3a283d2a3617dce93ac06398b5a40448707866facb4","target":"graph","created_at":"2026-07-05T04:57:24Z","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/2201.11403/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we develop a novel transformer-based generative adversarial neural network called U-Transformer for generalised image outpainting problem. Different from most present image outpainting methods conducting horizontal extrapolation, our generalised image outpainting could extrapolate visual context all-side around a given image with plausible structure and details even for complicated scenery, building, and art images. Specifically, we design a generator as an encoder-to-decoder structure embedded with the popular Swin Transformer blocks. As such, our novel neural network can bette","authors_text":"John Y. Goulermas, Kaizhu Huang, Penglei Gao, Rui Zhang, Xi Yang, Yujie Geng, Yuyao Yan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-01-27T09:41:58Z","title":"Generalised Image Outpainting with U-Transformer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.11403","kind":"arxiv","version":5},"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":"sha256:97972d40fb94edc3eca279a1af0c01b6144bd517e6d12735f7afb1ae65bf6fa4","target":"record","created_at":"2026-07-05T04:57:24Z","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":"9ed02d4734286b38c1210ddff406c23a5783be4a1fbb309e3470956ef9da42b5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-01-27T09:41:58Z","title_canon_sha256":"b4cb93b4b5a4e097ea2d17b9b3d2ea750257fca5ed1a4f67716aec4848bca782"},"schema_version":"1.0","source":{"id":"2201.11403","kind":"arxiv","version":5}},"canonical_sha256":"49fc448c852f0990198de7e9ea6bc54a19d5149f723f4c08a070824897c2129f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"49fc448c852f0990198de7e9ea6bc54a19d5149f723f4c08a070824897c2129f","first_computed_at":"2026-07-05T04:57:24.014063Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:57:24.014063Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5tX1O60yM44DVL4yLAmYMC0/0k1vP0XX7+76PAO1Qr2UAFzczUMtew0JAkg2U40YAeJpG2ZyZ3I4zNeswgpcBw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:57:24.014429Z","signed_message":"canonical_sha256_bytes"},"source_id":"2201.11403","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:97972d40fb94edc3eca279a1af0c01b6144bd517e6d12735f7afb1ae65bf6fa4","sha256:a41b1f60eb20a3041c5ae3a283d2a3617dce93ac06398b5a40448707866facb4"],"state_sha256":"7147025efe2de0f6b2bc7b0803faaa4a0489a1400ace2a12eb7717dd9ed6d03e"}