{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:V6ACA4O744MSII6KJPD4VVAP4R","short_pith_number":"pith:V6ACA4O7","canonical_record":{"source":{"id":"2106.06792","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-06-12T15:05:17Z","cross_cats_sorted":[],"title_canon_sha256":"04ab1c15a6bc5a26f8b4ac71e60c0987a908af6765a5b8328ea4954f273c577c","abstract_canon_sha256":"41e51e0f1e7c983cf2d23cf7ab64c521c146d6b24f3fb19a50e456aa1d4acd71"},"schema_version":"1.0"},"canonical_sha256":"af802071dfe7192423ca4bc7cad40fe4639cc9b06b8b090828c349485e28832e","source":{"kind":"arxiv","id":"2106.06792","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.06792","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"arxiv_version","alias_value":"2106.06792v1","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.06792","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"pith_short_12","alias_value":"V6ACA4O744MS","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"pith_short_16","alias_value":"V6ACA4O744MSII6K","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"pith_short_8","alias_value":"V6ACA4O7","created_at":"2026-07-05T02:48:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:V6ACA4O744MSII6KJPD4VVAP4R","target":"record","payload":{"canonical_record":{"source":{"id":"2106.06792","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-06-12T15:05:17Z","cross_cats_sorted":[],"title_canon_sha256":"04ab1c15a6bc5a26f8b4ac71e60c0987a908af6765a5b8328ea4954f273c577c","abstract_canon_sha256":"41e51e0f1e7c983cf2d23cf7ab64c521c146d6b24f3fb19a50e456aa1d4acd71"},"schema_version":"1.0"},"canonical_sha256":"af802071dfe7192423ca4bc7cad40fe4639cc9b06b8b090828c349485e28832e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:48:41.294429Z","signature_b64":"2tbTmmqnvUZSSbWy8SM+HRztLieETONXxtTY/kcgMBH3pNFdo6sjOL/p7GOBIgzdDjGoi7ZtQIQPuV31KSmBAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af802071dfe7192423ca4bc7cad40fe4639cc9b06b8b090828c349485e28832e","last_reissued_at":"2026-07-05T02:48:41.294028Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:48:41.294028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.06792","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:48:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RqQo/UA9xHh40r94w71qiDPO2MbD57DpU2l1NrIpwBPb6UKUiAzqPJazpsx4H90t1DkNVm8AEqx7yXpF/UcPDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T10:14:49.596822Z"},"content_sha256":"1479ba01f5c925df5c0c492a0e4a35495d88d478a2455422c19547be94cba7d9","schema_version":"1.0","event_id":"sha256:1479ba01f5c925df5c0c492a0e4a35495d88d478a2455422c19547be94cba7d9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:V6ACA4O744MSII6KJPD4VVAP4R","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A One-Shot Texture-Perceiving Generative Adversarial Network for Unsupervised Surface Inspection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Lingyun Gu, Lin Zhang, Zhaokui Wang","submitted_at":"2021-06-12T15:05:17Z","abstract_excerpt":"Visual surface inspection is a challenging task owing to the highly diverse appearance of target surfaces and defective regions. Previous attempts heavily rely on vast quantities of training examples with manual annotation. However, in some practical cases, it is difficult to obtain a large number of samples for inspection. To combat it, we propose a hierarchical texture-perceiving generative adversarial network (HTP-GAN) that is learned from the one-shot normal image in an unsupervised scheme. Specifically, the HTP-GAN contains a pyramid of convolutional GANs that can capture the global struc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.06792","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/2106.06792/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":"2026-07-05T02:48:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2q4uwkO9PGUCzoy60KvwwSFzOAH5aaGMQ/vjYfd6/V72G5QR/L1FijO36BWR2Yg+k18JZj9qb4s58pKLX3ndCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T10:14:49.598013Z"},"content_sha256":"1ab4e52477ea3f0d18696fb675aa20892a31b0e52acb09d2969fc69e2649c800","schema_version":"1.0","event_id":"sha256:1ab4e52477ea3f0d18696fb675aa20892a31b0e52acb09d2969fc69e2649c800"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V6ACA4O744MSII6KJPD4VVAP4R/bundle.json","state_url":"https://pith.science/pith/V6ACA4O744MSII6KJPD4VVAP4R/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V6ACA4O744MSII6KJPD4VVAP4R/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":"2026-08-11T10:14:49Z","links":{"resolver":"https://pith.science/pith/V6ACA4O744MSII6KJPD4VVAP4R","bundle":"https://pith.science/pith/V6ACA4O744MSII6KJPD4VVAP4R/bundle.json","state":"https://pith.science/pith/V6ACA4O744MSII6KJPD4VVAP4R/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V6ACA4O744MSII6KJPD4VVAP4R/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:V6ACA4O744MSII6KJPD4VVAP4R","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":"41e51e0f1e7c983cf2d23cf7ab64c521c146d6b24f3fb19a50e456aa1d4acd71","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-06-12T15:05:17Z","title_canon_sha256":"04ab1c15a6bc5a26f8b4ac71e60c0987a908af6765a5b8328ea4954f273c577c"},"schema_version":"1.0","source":{"id":"2106.06792","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.06792","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"arxiv_version","alias_value":"2106.06792v1","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.06792","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"pith_short_12","alias_value":"V6ACA4O744MS","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"pith_short_16","alias_value":"V6ACA4O744MSII6K","created_at":"2026-07-05T02:48:41Z"},{"alias_kind":"pith_short_8","alias_value":"V6ACA4O7","created_at":"2026-07-05T02:48:41Z"}],"graph_snapshots":[{"event_id":"sha256:1ab4e52477ea3f0d18696fb675aa20892a31b0e52acb09d2969fc69e2649c800","target":"graph","created_at":"2026-07-05T02:48:41Z","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/2106.06792/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Visual surface inspection is a challenging task owing to the highly diverse appearance of target surfaces and defective regions. Previous attempts heavily rely on vast quantities of training examples with manual annotation. However, in some practical cases, it is difficult to obtain a large number of samples for inspection. To combat it, we propose a hierarchical texture-perceiving generative adversarial network (HTP-GAN) that is learned from the one-shot normal image in an unsupervised scheme. Specifically, the HTP-GAN contains a pyramid of convolutional GANs that can capture the global struc","authors_text":"Lingyun Gu, Lin Zhang, Zhaokui Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-06-12T15:05:17Z","title":"A One-Shot Texture-Perceiving Generative Adversarial Network for Unsupervised Surface Inspection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.06792","kind":"arxiv","version":1},"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":"sha256:1479ba01f5c925df5c0c492a0e4a35495d88d478a2455422c19547be94cba7d9","target":"record","created_at":"2026-07-05T02:48:41Z","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":"41e51e0f1e7c983cf2d23cf7ab64c521c146d6b24f3fb19a50e456aa1d4acd71","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-06-12T15:05:17Z","title_canon_sha256":"04ab1c15a6bc5a26f8b4ac71e60c0987a908af6765a5b8328ea4954f273c577c"},"schema_version":"1.0","source":{"id":"2106.06792","kind":"arxiv","version":1}},"canonical_sha256":"af802071dfe7192423ca4bc7cad40fe4639cc9b06b8b090828c349485e28832e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af802071dfe7192423ca4bc7cad40fe4639cc9b06b8b090828c349485e28832e","first_computed_at":"2026-07-05T02:48:41.294028Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:48:41.294028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2tbTmmqnvUZSSbWy8SM+HRztLieETONXxtTY/kcgMBH3pNFdo6sjOL/p7GOBIgzdDjGoi7ZtQIQPuV31KSmBAw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:48:41.294429Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.06792","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1479ba01f5c925df5c0c492a0e4a35495d88d478a2455422c19547be94cba7d9","sha256:1ab4e52477ea3f0d18696fb675aa20892a31b0e52acb09d2969fc69e2649c800"],"state_sha256":"ef1e0c2816cfb547940ab96493fb9e564004ca22174a361ad750380ef6d7f5d3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5xVFMSgualkQi2DggCZSJsRm8KyOwM5tg4EC+dudbv5Aik/r2APUK35bK6ApMb09qMEpOpo7oKMH9ejVK5sHBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T10:14:49.604075Z","bundle_sha256":"a39a5982ec06b3a628ee6201181106c08a3cfa64582742c43e4ac8bb19fa831b"}}