{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:XPHXMG3QTHQUGQFGB6N66GS46T","short_pith_number":"pith:XPHXMG3Q","schema_version":"1.0","canonical_sha256":"bbcf761b7099e14340a60f9bef1a5cf4e506c40196abc2a91feaed1bbe6953eb","source":{"kind":"arxiv","id":"2405.06283","version":1},"attestation_state":"computed","paper":{"title":"Novel Class Discovery for Ultra-Fine-Grained Visual Categorization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Binglin Qiu, Nan Pu, Qi Jia, Weimin Wang, Yaqi Cai, Yu Liu","submitted_at":"2024-05-10T07:31:11Z","abstract_excerpt":"Ultra-fine-grained visual categorization (Ultra-FGVC) aims at distinguishing highly similar sub-categories within fine-grained objects, such as different soybean cultivars. Compared to traditional fine-grained visual categorization, Ultra-FGVC encounters more hurdles due to the small inter-class and large intra-class variation. Given these challenges, relying on human annotation for Ultra-FGVC is impractical. To this end, our work introduces a novel task termed Ultra-Fine-Grained Novel Class Discovery (UFG-NCD), which leverages partially annotated data to identify new categories of unlabeled i"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2405.06283","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-05-10T07:31:11Z","cross_cats_sorted":[],"title_canon_sha256":"cc540171be96525025e4e7c3ee7bc964f6faca1443115dfaccdb682395e848ba","abstract_canon_sha256":"844292cf2ed5abc2ed6edcd3fa34fbfb1083bd4ada6f5657ade2b370cfc6fcc0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:17:38.504278Z","signature_b64":"vPfcKrqmgvQBnQT+XuC1kVInJK/HKYeGZmP8JLE1j6nEvEm+E0fhd2B9CSR4mUKtZHXfv8O3cpBAY0u9owKiAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bbcf761b7099e14340a60f9bef1a5cf4e506c40196abc2a91feaed1bbe6953eb","last_reissued_at":"2026-07-05T08:17:38.503843Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:17:38.503843Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Novel Class Discovery for Ultra-Fine-Grained Visual Categorization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Binglin Qiu, Nan Pu, Qi Jia, Weimin Wang, Yaqi Cai, Yu Liu","submitted_at":"2024-05-10T07:31:11Z","abstract_excerpt":"Ultra-fine-grained visual categorization (Ultra-FGVC) aims at distinguishing highly similar sub-categories within fine-grained objects, such as different soybean cultivars. Compared to traditional fine-grained visual categorization, Ultra-FGVC encounters more hurdles due to the small inter-class and large intra-class variation. Given these challenges, relying on human annotation for Ultra-FGVC is impractical. To this end, our work introduces a novel task termed Ultra-Fine-Grained Novel Class Discovery (UFG-NCD), which leverages partially annotated data to identify new categories of unlabeled i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.06283","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/2405.06283/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2405.06283","created_at":"2026-07-05T08:17:38.503890+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.06283v1","created_at":"2026-07-05T08:17:38.503890+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.06283","created_at":"2026-07-05T08:17:38.503890+00:00"},{"alias_kind":"pith_short_12","alias_value":"XPHXMG3QTHQU","created_at":"2026-07-05T08:17:38.503890+00:00"},{"alias_kind":"pith_short_16","alias_value":"XPHXMG3QTHQUGQFG","created_at":"2026-07-05T08:17:38.503890+00:00"},{"alias_kind":"pith_short_8","alias_value":"XPHXMG3Q","created_at":"2026-07-05T08:17:38.503890+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XPHXMG3QTHQUGQFGB6N66GS46T","json":"https://pith.science/pith/XPHXMG3QTHQUGQFGB6N66GS46T.json","graph_json":"https://pith.science/api/pith-number/XPHXMG3QTHQUGQFGB6N66GS46T/graph.json","events_json":"https://pith.science/api/pith-number/XPHXMG3QTHQUGQFGB6N66GS46T/events.json","paper":"https://pith.science/paper/XPHXMG3Q"},"agent_actions":{"view_html":"https://pith.science/pith/XPHXMG3QTHQUGQFGB6N66GS46T","download_json":"https://pith.science/pith/XPHXMG3QTHQUGQFGB6N66GS46T.json","view_paper":"https://pith.science/paper/XPHXMG3Q","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.06283&json=true","fetch_graph":"https://pith.science/api/pith-number/XPHXMG3QTHQUGQFGB6N66GS46T/graph.json","fetch_events":"https://pith.science/api/pith-number/XPHXMG3QTHQUGQFGB6N66GS46T/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XPHXMG3QTHQUGQFGB6N66GS46T/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XPHXMG3QTHQUGQFGB6N66GS46T/action/storage_attestation","attest_author":"https://pith.science/pith/XPHXMG3QTHQUGQFGB6N66GS46T/action/author_attestation","sign_citation":"https://pith.science/pith/XPHXMG3QTHQUGQFGB6N66GS46T/action/citation_signature","submit_replication":"https://pith.science/pith/XPHXMG3QTHQUGQFGB6N66GS46T/action/replication_record"}},"created_at":"2026-07-05T08:17:38.503890+00:00","updated_at":"2026-07-05T08:17:38.503890+00:00"}