{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:HSNPB3UZFXSIDXZG473MD3VJG3","short_pith_number":"pith:HSNPB3UZ","canonical_record":{"source":{"id":"1810.12155","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:37:29Z","cross_cats_sorted":[],"title_canon_sha256":"cdf1f22bb4e2db6937f19fb84a66560ef8f4aa8515e3334fe5c4cf55873314c9","abstract_canon_sha256":"78b5ac5027d722cbc38baaa288224d374c4b58f10b20d3165066bffc5ee0e8f8"},"schema_version":"1.0"},"canonical_sha256":"3c9af0ee992de481df26e7f6c1eea936f9ea98dabf2660e039ebccaac7605a5a","source":{"kind":"arxiv","id":"1810.12155","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.12155","created_at":"2026-05-18T00:02:04Z"},{"alias_kind":"arxiv_version","alias_value":"1810.12155v1","created_at":"2026-05-18T00:02:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.12155","created_at":"2026-05-18T00:02:04Z"},{"alias_kind":"pith_short_12","alias_value":"HSNPB3UZFXSI","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HSNPB3UZFXSIDXZG","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HSNPB3UZ","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:HSNPB3UZFXSIDXZG473MD3VJG3","target":"record","payload":{"canonical_record":{"source":{"id":"1810.12155","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:37:29Z","cross_cats_sorted":[],"title_canon_sha256":"cdf1f22bb4e2db6937f19fb84a66560ef8f4aa8515e3334fe5c4cf55873314c9","abstract_canon_sha256":"78b5ac5027d722cbc38baaa288224d374c4b58f10b20d3165066bffc5ee0e8f8"},"schema_version":"1.0"},"canonical_sha256":"3c9af0ee992de481df26e7f6c1eea936f9ea98dabf2660e039ebccaac7605a5a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:02:04.120049Z","signature_b64":"+4Hua3MoZdUdhDeat9eHqrk6/Rd3LoDcDY2LtNZmOzlAumTLaijBZvTYpV08zy8ptjVkdKNGp+rY0oJMSOPyBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c9af0ee992de481df26e7f6c1eea936f9ea98dabf2660e039ebccaac7605a5a","last_reissued_at":"2026-05-18T00:02:04.119269Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:02:04.119269Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.12155","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":"2026-05-18T00:02:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V2C2K4nFgiO0gZssLC+seK2BixiD6efz2iO7Hwm2VbK2RhZ39qgjJGXG6R0AiVSZ4PQTLeFuDQClJsKZ6b2oDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T06:49:33.916715Z"},"content_sha256":"fd4f03ac17456d43cf074e515995a148f9579c460340b0b09a683184ce7b2b2b","schema_version":"1.0","event_id":"sha256:fd4f03ac17456d43cf074e515995a148f9579c460340b0b09a683184ce7b2b2b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:HSNPB3UZFXSIDXZG473MD3VJG3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Recurrent Transformer Networks for Semantic Correspondence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dongbo Min, Kwanghoon Sohn, Sangryul Jeon, Seungryong Kim, Stephen Lin","submitted_at":"2018-10-29T14:37:29Z","abstract_excerpt":"We present recurrent transformer networks (RTNs) for obtaining dense correspondences between semantically similar images. Our networks accomplish this through an iterative process of estimating spatial transformations between the input images and using these transformations to generate aligned convolutional activations. By directly estimating the transformations between an image pair, rather than employing spatial transformer networks to independently normalize each individual image, we show that greater accuracy can be achieved. This process is conducted in a recursive manner to refine both t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.12155","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":""},"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":"2026-05-18T00:02:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jd9XvO3O63gUhJa/IhJKqn54tG9dYVrmQBOiEgW6u/cyQh6clC2298taaLp38lk8+lvUse7LrguNN/MyFeshCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T06:49:33.917056Z"},"content_sha256":"d7007d040ab569dba3bf63916bb4cf7513a098787cbaef400f177a959fb551d7","schema_version":"1.0","event_id":"sha256:d7007d040ab569dba3bf63916bb4cf7513a098787cbaef400f177a959fb551d7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HSNPB3UZFXSIDXZG473MD3VJG3/bundle.json","state_url":"https://pith.science/pith/HSNPB3UZFXSIDXZG473MD3VJG3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HSNPB3UZFXSIDXZG473MD3VJG3/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":"2026-06-28T06:49:33Z","links":{"resolver":"https://pith.science/pith/HSNPB3UZFXSIDXZG473MD3VJG3","bundle":"https://pith.science/pith/HSNPB3UZFXSIDXZG473MD3VJG3/bundle.json","state":"https://pith.science/pith/HSNPB3UZFXSIDXZG473MD3VJG3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HSNPB3UZFXSIDXZG473MD3VJG3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:HSNPB3UZFXSIDXZG473MD3VJG3","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":"78b5ac5027d722cbc38baaa288224d374c4b58f10b20d3165066bffc5ee0e8f8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:37:29Z","title_canon_sha256":"cdf1f22bb4e2db6937f19fb84a66560ef8f4aa8515e3334fe5c4cf55873314c9"},"schema_version":"1.0","source":{"id":"1810.12155","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.12155","created_at":"2026-05-18T00:02:04Z"},{"alias_kind":"arxiv_version","alias_value":"1810.12155v1","created_at":"2026-05-18T00:02:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.12155","created_at":"2026-05-18T00:02:04Z"},{"alias_kind":"pith_short_12","alias_value":"HSNPB3UZFXSI","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HSNPB3UZFXSIDXZG","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HSNPB3UZ","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:d7007d040ab569dba3bf63916bb4cf7513a098787cbaef400f177a959fb551d7","target":"graph","created_at":"2026-05-18T00:02:04Z","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"},"paper":{"abstract_excerpt":"We present recurrent transformer networks (RTNs) for obtaining dense correspondences between semantically similar images. Our networks accomplish this through an iterative process of estimating spatial transformations between the input images and using these transformations to generate aligned convolutional activations. By directly estimating the transformations between an image pair, rather than employing spatial transformer networks to independently normalize each individual image, we show that greater accuracy can be achieved. This process is conducted in a recursive manner to refine both t","authors_text":"Dongbo Min, Kwanghoon Sohn, Sangryul Jeon, Seungryong Kim, Stephen Lin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:37:29Z","title":"Recurrent Transformer Networks for Semantic Correspondence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.12155","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:fd4f03ac17456d43cf074e515995a148f9579c460340b0b09a683184ce7b2b2b","target":"record","created_at":"2026-05-18T00:02:04Z","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":"78b5ac5027d722cbc38baaa288224d374c4b58f10b20d3165066bffc5ee0e8f8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-29T14:37:29Z","title_canon_sha256":"cdf1f22bb4e2db6937f19fb84a66560ef8f4aa8515e3334fe5c4cf55873314c9"},"schema_version":"1.0","source":{"id":"1810.12155","kind":"arxiv","version":1}},"canonical_sha256":"3c9af0ee992de481df26e7f6c1eea936f9ea98dabf2660e039ebccaac7605a5a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3c9af0ee992de481df26e7f6c1eea936f9ea98dabf2660e039ebccaac7605a5a","first_computed_at":"2026-05-18T00:02:04.119269Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:02:04.119269Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+4Hua3MoZdUdhDeat9eHqrk6/Rd3LoDcDY2LtNZmOzlAumTLaijBZvTYpV08zy8ptjVkdKNGp+rY0oJMSOPyBA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:02:04.120049Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.12155","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fd4f03ac17456d43cf074e515995a148f9579c460340b0b09a683184ce7b2b2b","sha256:d7007d040ab569dba3bf63916bb4cf7513a098787cbaef400f177a959fb551d7"],"state_sha256":"5d06826112ce30abaaa4eb8b62cd6114664ae9d314c67b4b74e0ac89e8ff7596"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"88gSP8hGQ7d5wOwIN7eV41PVdiZ0Bijy6nRD4GnbgWO4f131Sfu2bqqM4o57TQgFkvubWEG4xe8UWKC2fPnwDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T06:49:33.918920Z","bundle_sha256":"81dff9f2b6e9e99134d80f63d2a3e8c5b83a04544dbcb7601a7cafe46959fd29"}}