{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:5EMETKO762ZJ3U35IZYBFBO22L","short_pith_number":"pith:5EMETKO7","canonical_record":{"source":{"id":"2103.13990","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-03-25T17:27:08Z","cross_cats_sorted":[],"title_canon_sha256":"83b4af5326ffb0a14a9e9821a635ecb5f019adf7cd08c2ce17b96746a3a9f039","abstract_canon_sha256":"9303a7cef147818b6c65a8999ede31ebb25f501b0de4f8a668f1ed4273988291"},"schema_version":"1.0"},"canonical_sha256":"e91849a9dff6b29dd37d46701285dad2d46d9c8570f755d0d5af1107d619570d","source":{"kind":"arxiv","id":"2103.13990","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.13990","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"arxiv_version","alias_value":"2103.13990v1","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.13990","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"pith_short_12","alias_value":"5EMETKO762ZJ","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"pith_short_16","alias_value":"5EMETKO762ZJ3U35","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"pith_short_8","alias_value":"5EMETKO7","created_at":"2026-07-05T02:26:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:5EMETKO762ZJ3U35IZYBFBO22L","target":"record","payload":{"canonical_record":{"source":{"id":"2103.13990","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-03-25T17:27:08Z","cross_cats_sorted":[],"title_canon_sha256":"83b4af5326ffb0a14a9e9821a635ecb5f019adf7cd08c2ce17b96746a3a9f039","abstract_canon_sha256":"9303a7cef147818b6c65a8999ede31ebb25f501b0de4f8a668f1ed4273988291"},"schema_version":"1.0"},"canonical_sha256":"e91849a9dff6b29dd37d46701285dad2d46d9c8570f755d0d5af1107d619570d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:26:24.465622Z","signature_b64":"EeeWK/Hm7sL6EyFufcXaFJd9EYkxsfHLLrXedvTrWPl0ogRI8Qh1OfREQMMjuQQIt6X9AV4jHeTlUjqMKs0GCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e91849a9dff6b29dd37d46701285dad2d46d9c8570f755d0d5af1107d619570d","last_reissued_at":"2026-07-05T02:26:24.465170Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:26:24.465170Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2103.13990","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":"2026-07-05T02:26:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hPTONQKESrpTil75SQIXjhcsj9fwwFtZqRoroKzDrsSWOmAmK5lDc3cJRNM+Jhxd9kUJdzaaxHeVWzzFZ48ZAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T09:46:43.699245Z"},"content_sha256":"b0b61a76ed76dcb22d2a600ead8cd613eded7c9fba62e5400726a2047b74a303","schema_version":"1.0","event_id":"sha256:b0b61a76ed76dcb22d2a600ead8cd613eded7c9fba62e5400726a2047b74a303"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:5EMETKO762ZJ3U35IZYBFBO22L","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aneeshan Sain, Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Tao Xiang, Yi-Zhe Song, Yongxin Yang","submitted_at":"2021-03-25T17:27:08Z","abstract_excerpt":"A fundamental challenge faced by existing Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) models is the data scarcity -- model performances are largely bottlenecked by the lack of sketch-photo pairs. Whilst the number of photos can be easily scaled, each corresponding sketch still needs to be individually produced. In this paper, we aim to mitigate such an upper-bound on sketch data, and study whether unlabelled photos alone (of which they are many) can be cultivated for performances gain. In particular, we introduce a novel semi-supervised framework for cross-modal retrieval that can addi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.13990","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/2103.13990/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":"2026-07-05T02:26:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aGZbggPbJ8rjDw0k4hTL4oiL7pXPy4+I/02av/YNbre0vAV0TNRqkqEdvWG6v7i2nJEH1TavQTZhxLtuDSJ7Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T09:46:43.699742Z"},"content_sha256":"0cc772c10d60963883b4002e1bd01f8d28c555c930ebe0c902061c804bc5240a","schema_version":"1.0","event_id":"sha256:0cc772c10d60963883b4002e1bd01f8d28c555c930ebe0c902061c804bc5240a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5EMETKO762ZJ3U35IZYBFBO22L/bundle.json","state_url":"https://pith.science/pith/5EMETKO762ZJ3U35IZYBFBO22L/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5EMETKO762ZJ3U35IZYBFBO22L/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":"2026-08-11T09:46:43Z","links":{"resolver":"https://pith.science/pith/5EMETKO762ZJ3U35IZYBFBO22L","bundle":"https://pith.science/pith/5EMETKO762ZJ3U35IZYBFBO22L/bundle.json","state":"https://pith.science/pith/5EMETKO762ZJ3U35IZYBFBO22L/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5EMETKO762ZJ3U35IZYBFBO22L/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:5EMETKO762ZJ3U35IZYBFBO22L","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":"9303a7cef147818b6c65a8999ede31ebb25f501b0de4f8a668f1ed4273988291","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-03-25T17:27:08Z","title_canon_sha256":"83b4af5326ffb0a14a9e9821a635ecb5f019adf7cd08c2ce17b96746a3a9f039"},"schema_version":"1.0","source":{"id":"2103.13990","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.13990","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"arxiv_version","alias_value":"2103.13990v1","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.13990","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"pith_short_12","alias_value":"5EMETKO762ZJ","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"pith_short_16","alias_value":"5EMETKO762ZJ3U35","created_at":"2026-07-05T02:26:24Z"},{"alias_kind":"pith_short_8","alias_value":"5EMETKO7","created_at":"2026-07-05T02:26:24Z"}],"graph_snapshots":[{"event_id":"sha256:0cc772c10d60963883b4002e1bd01f8d28c555c930ebe0c902061c804bc5240a","target":"graph","created_at":"2026-07-05T02:26:24Z","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/2103.13990/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A fundamental challenge faced by existing Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) models is the data scarcity -- model performances are largely bottlenecked by the lack of sketch-photo pairs. Whilst the number of photos can be easily scaled, each corresponding sketch still needs to be individually produced. In this paper, we aim to mitigate such an upper-bound on sketch data, and study whether unlabelled photos alone (of which they are many) can be cultivated for performances gain. In particular, we introduce a novel semi-supervised framework for cross-modal retrieval that can addi","authors_text":"Aneeshan Sain, Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Tao Xiang, Yi-Zhe Song, Yongxin Yang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-03-25T17:27:08Z","title":"More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.13990","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:b0b61a76ed76dcb22d2a600ead8cd613eded7c9fba62e5400726a2047b74a303","target":"record","created_at":"2026-07-05T02:26:24Z","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":"9303a7cef147818b6c65a8999ede31ebb25f501b0de4f8a668f1ed4273988291","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-03-25T17:27:08Z","title_canon_sha256":"83b4af5326ffb0a14a9e9821a635ecb5f019adf7cd08c2ce17b96746a3a9f039"},"schema_version":"1.0","source":{"id":"2103.13990","kind":"arxiv","version":1}},"canonical_sha256":"e91849a9dff6b29dd37d46701285dad2d46d9c8570f755d0d5af1107d619570d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e91849a9dff6b29dd37d46701285dad2d46d9c8570f755d0d5af1107d619570d","first_computed_at":"2026-07-05T02:26:24.465170Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:26:24.465170Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EeeWK/Hm7sL6EyFufcXaFJd9EYkxsfHLLrXedvTrWPl0ogRI8Qh1OfREQMMjuQQIt6X9AV4jHeTlUjqMKs0GCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:26:24.465622Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.13990","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b0b61a76ed76dcb22d2a600ead8cd613eded7c9fba62e5400726a2047b74a303","sha256:0cc772c10d60963883b4002e1bd01f8d28c555c930ebe0c902061c804bc5240a"],"state_sha256":"8677b4da91b9753e7709dacbff55730b68c6816e3ea96a7693a869196573324e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C9lDPdlBycXrhPADw9I4c5Ye3Ku5ogEEFkk7CMjLhyz2THpA4WEgrsF+QQOMDRV3tE9GX5oFb6w6+BTDsSPFCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T09:46:43.704652Z","bundle_sha256":"acd15ced1aa988d41bbe0e8e3de1ba7a40e079ea40f2aa2e9c867eb84b1a606a"}}