{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:MQKALR5ODUYVM75BLORS5B235T","short_pith_number":"pith:MQKALR5O","canonical_record":{"source":{"id":"2508.05068","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-07T06:41:31Z","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"title_canon_sha256":"8aedf7ed590211b26b68ae798bcb02bc5fa803d4ee751238ebaa100fddcd6a99","abstract_canon_sha256":"6074ac1470a66d13437ca28f6cbd1f5dfc1d9df5033009a5e00771d9d71dc132"},"schema_version":"1.0"},"canonical_sha256":"641405c7ae1d31567fa15ba32e875becfc8a3d999d9979ed8b0c1cf881b47ff6","source":{"kind":"arxiv","id":"2508.05068","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.05068","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"arxiv_version","alias_value":"2508.05068v2","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.05068","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"pith_short_12","alias_value":"MQKALR5ODUYV","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"pith_short_16","alias_value":"MQKALR5ODUYVM75B","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"pith_short_8","alias_value":"MQKALR5O","created_at":"2026-07-05T11:55:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:MQKALR5ODUYVM75BLORS5B235T","target":"record","payload":{"canonical_record":{"source":{"id":"2508.05068","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-07T06:41:31Z","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"title_canon_sha256":"8aedf7ed590211b26b68ae798bcb02bc5fa803d4ee751238ebaa100fddcd6a99","abstract_canon_sha256":"6074ac1470a66d13437ca28f6cbd1f5dfc1d9df5033009a5e00771d9d71dc132"},"schema_version":"1.0"},"canonical_sha256":"641405c7ae1d31567fa15ba32e875becfc8a3d999d9979ed8b0c1cf881b47ff6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:55:42.014322Z","signature_b64":"2zSx15wJAUfWeO9Zvfk3bgfcsUtV/11wkY5WZ62saKvfdrZh89aFPWxpp2NSOsfuNft9BqCOt4+sPwPLB3xfCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"641405c7ae1d31567fa15ba32e875becfc8a3d999d9979ed8b0c1cf881b47ff6","last_reissued_at":"2026-07-05T11:55:42.013858Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:55:42.013858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.05068","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:55:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5nuC7UsvljwTh6pkPZvw+a2n2+jHld+JUEemznlirOSIsZ0yATvRT/DGUTbz6oHoZTwd08JdnDKjlG2lQ3bNDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T00:11:02.913021Z"},"content_sha256":"e07c4fe63d6e38927a3dbc201d6162b14a8048de0755cdb0054cb35013677c3e","schema_version":"1.0","event_id":"sha256:e07c4fe63d6e38927a3dbc201d6162b14a8048de0755cdb0054cb35013677c3e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:MQKALR5ODUYVM75BLORS5B235T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automatic Image Colorization with Convolutional Neural Networks and Generative Adversarial Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","eess.IV"],"primary_cat":"cs.CV","authors_text":"Changyuan Qiu, Hangrui Cao, Qihan Ren, Ruiyu Li, Yuqing Qiu","submitted_at":"2025-08-07T06:41:31Z","abstract_excerpt":"Image colorization, the task of adding colors to grayscale images, has been the focus of significant research efforts in computer vision in recent years for its various application areas such as color restoration and automatic animation colorization [15, 1]. The colorization problem is challenging as it is highly ill-posed with two out of three image dimensions lost, resulting in large degrees of freedom. However, semantics of the scene as well as the surface texture could provide important cues for colors: the sky is typically blue, the clouds are typically white and the grass is typically gr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.05068","kind":"arxiv","version":2},"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/2508.05068/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":"2026-07-05T11:55:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"73HlxZTZb90MKaYhgnjWAb8+xWGMxlzs2Cf7gDUlsVs2U4aamErW3pIMxmwSR9B1ou4CNSo43ftWWFhLV3KnBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T00:11:02.914024Z"},"content_sha256":"4e74dad4de931d0e48a5fccab1eedbf86e9f6036f16eeff297d5fc4dd231b21d","schema_version":"1.0","event_id":"sha256:4e74dad4de931d0e48a5fccab1eedbf86e9f6036f16eeff297d5fc4dd231b21d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MQKALR5ODUYVM75BLORS5B235T/bundle.json","state_url":"https://pith.science/pith/MQKALR5ODUYVM75BLORS5B235T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MQKALR5ODUYVM75BLORS5B235T/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":"2026-08-13T00:11:02Z","links":{"resolver":"https://pith.science/pith/MQKALR5ODUYVM75BLORS5B235T","bundle":"https://pith.science/pith/MQKALR5ODUYVM75BLORS5B235T/bundle.json","state":"https://pith.science/pith/MQKALR5ODUYVM75BLORS5B235T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MQKALR5ODUYVM75BLORS5B235T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MQKALR5ODUYVM75BLORS5B235T","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":"6074ac1470a66d13437ca28f6cbd1f5dfc1d9df5033009a5e00771d9d71dc132","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-07T06:41:31Z","title_canon_sha256":"8aedf7ed590211b26b68ae798bcb02bc5fa803d4ee751238ebaa100fddcd6a99"},"schema_version":"1.0","source":{"id":"2508.05068","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.05068","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"arxiv_version","alias_value":"2508.05068v2","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.05068","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"pith_short_12","alias_value":"MQKALR5ODUYV","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"pith_short_16","alias_value":"MQKALR5ODUYVM75B","created_at":"2026-07-05T11:55:42Z"},{"alias_kind":"pith_short_8","alias_value":"MQKALR5O","created_at":"2026-07-05T11:55:42Z"}],"graph_snapshots":[{"event_id":"sha256:4e74dad4de931d0e48a5fccab1eedbf86e9f6036f16eeff297d5fc4dd231b21d","target":"graph","created_at":"2026-07-05T11:55:42Z","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/2508.05068/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Image colorization, the task of adding colors to grayscale images, has been the focus of significant research efforts in computer vision in recent years for its various application areas such as color restoration and automatic animation colorization [15, 1]. The colorization problem is challenging as it is highly ill-posed with two out of three image dimensions lost, resulting in large degrees of freedom. However, semantics of the scene as well as the surface texture could provide important cues for colors: the sky is typically blue, the clouds are typically white and the grass is typically gr","authors_text":"Changyuan Qiu, Hangrui Cao, Qihan Ren, Ruiyu Li, Yuqing Qiu","cross_cats":["cs.AI","cs.LG","eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-07T06:41:31Z","title":"Automatic Image Colorization with Convolutional Neural Networks and Generative Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.05068","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:e07c4fe63d6e38927a3dbc201d6162b14a8048de0755cdb0054cb35013677c3e","target":"record","created_at":"2026-07-05T11:55:42Z","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":"6074ac1470a66d13437ca28f6cbd1f5dfc1d9df5033009a5e00771d9d71dc132","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-07T06:41:31Z","title_canon_sha256":"8aedf7ed590211b26b68ae798bcb02bc5fa803d4ee751238ebaa100fddcd6a99"},"schema_version":"1.0","source":{"id":"2508.05068","kind":"arxiv","version":2}},"canonical_sha256":"641405c7ae1d31567fa15ba32e875becfc8a3d999d9979ed8b0c1cf881b47ff6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"641405c7ae1d31567fa15ba32e875becfc8a3d999d9979ed8b0c1cf881b47ff6","first_computed_at":"2026-07-05T11:55:42.013858Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:55:42.013858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2zSx15wJAUfWeO9Zvfk3bgfcsUtV/11wkY5WZ62saKvfdrZh89aFPWxpp2NSOsfuNft9BqCOt4+sPwPLB3xfCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:55:42.014322Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.05068","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e07c4fe63d6e38927a3dbc201d6162b14a8048de0755cdb0054cb35013677c3e","sha256:4e74dad4de931d0e48a5fccab1eedbf86e9f6036f16eeff297d5fc4dd231b21d"],"state_sha256":"5e169c32559b4fc8a06b31c82985e7580d48d6245a6bf4e0d1b64e463a78b4b7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oMq90IpcCsMG/yY6WTYI9ppTyKeMKPWObgEwPaIGrbLzPd0Take4J7zIYSvr73DcEvIYCxaFKaDvWbj4ueeLCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T00:11:02.930283Z","bundle_sha256":"c636a6e14b03e685f6f865a4481504a3242042c1f34b96a6892e96fdd08557f4"}}