{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:VTLF2SF3LYPEGT7F7Z2FOZ2FVE","short_pith_number":"pith:VTLF2SF3","canonical_record":{"source":{"id":"2105.07637","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-17T06:49:29Z","cross_cats_sorted":[],"title_canon_sha256":"864f856704878893925604125f4455b3ef7b5209da3201f95aed14dafdcfcbde","abstract_canon_sha256":"ec18ef8c797bc5d856fbbc85c81a3875b69f53ea2a23c262a8ecd6b0fbfa61c8"},"schema_version":"1.0"},"canonical_sha256":"acd65d48bb5e1e434fe5fe74576745a921408b3dab4882307265d4e95d6c3a7e","source":{"kind":"arxiv","id":"2105.07637","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.07637","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"arxiv_version","alias_value":"2105.07637v2","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.07637","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"pith_short_12","alias_value":"VTLF2SF3LYPE","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"pith_short_16","alias_value":"VTLF2SF3LYPEGT7F","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"pith_short_8","alias_value":"VTLF2SF3","created_at":"2026-07-05T03:44:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:VTLF2SF3LYPEGT7F7Z2FOZ2FVE","target":"record","payload":{"canonical_record":{"source":{"id":"2105.07637","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-17T06:49:29Z","cross_cats_sorted":[],"title_canon_sha256":"864f856704878893925604125f4455b3ef7b5209da3201f95aed14dafdcfcbde","abstract_canon_sha256":"ec18ef8c797bc5d856fbbc85c81a3875b69f53ea2a23c262a8ecd6b0fbfa61c8"},"schema_version":"1.0"},"canonical_sha256":"acd65d48bb5e1e434fe5fe74576745a921408b3dab4882307265d4e95d6c3a7e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:44:10.389859Z","signature_b64":"mYxguAXZzembvlBzT6LP1eH2iV+HRyrfQxXWBb1/MHFqtazk/UTlseVtU8WP5UIo+rRWRcHOW9mejL1xI1APCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"acd65d48bb5e1e434fe5fe74576745a921408b3dab4882307265d4e95d6c3a7e","last_reissued_at":"2026-07-05T03:44:10.389401Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:44:10.389401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2105.07637","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":"2026-07-05T03:44:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WldXJe+UTDNzBz9VKPJfSsZ8cAohOp1uTu3NJtkaGCJIzy9A7LjvagFqg04UGx8sI5h8muhw6J/UcSCru3b3DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T02:37:14.269851Z"},"content_sha256":"b00ec4022d6b8e300d2c8e1957f1daf23df931fe43091f9c147c0f93894dca0b","schema_version":"1.0","event_id":"sha256:b00ec4022d6b8e300d2c8e1957f1daf23df931fe43091f9c147c0f93894dca0b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:VTLF2SF3LYPEGT7F7Z2FOZ2FVE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Class-Incremental Few-Shot Object Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Donghui Wang, Han Cui, Pengyang Li, Yanan Li","submitted_at":"2021-05-17T06:49:29Z","abstract_excerpt":"Conventional detection networks usually need abundant labeled training samples, while humans can learn new concepts incrementally with just a few examples. This paper focuses on a more challenging but realistic class-incremental few-shot object detection problem (iFSD). It aims to incrementally transfer the model for novel objects from only a few annotated samples without catastrophically forgetting the previously learned ones. To tackle this problem, we propose a novel method LEAST, which can transfer with Less forgetting, fEwer training resources, And Stronger Transfer capability. Specifical"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.07637","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/2105.07637/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":"2026-07-05T03:44:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GYEyZ3g9G4/WrxcSX4LnqhEH1B+ZNaCl2Ulljc9LvNmRWCr4Hav5oPszZsNCSaz7uB/1ZQsObyBomTbg4xsNBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T02:37:14.270524Z"},"content_sha256":"892b4e7a0403e335ad309ea6f9e20f5441a3e135b3d7a0a0b9474df522c36841","schema_version":"1.0","event_id":"sha256:892b4e7a0403e335ad309ea6f9e20f5441a3e135b3d7a0a0b9474df522c36841"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VTLF2SF3LYPEGT7F7Z2FOZ2FVE/bundle.json","state_url":"https://pith.science/pith/VTLF2SF3LYPEGT7F7Z2FOZ2FVE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VTLF2SF3LYPEGT7F7Z2FOZ2FVE/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":"2026-08-20T02:37:14Z","links":{"resolver":"https://pith.science/pith/VTLF2SF3LYPEGT7F7Z2FOZ2FVE","bundle":"https://pith.science/pith/VTLF2SF3LYPEGT7F7Z2FOZ2FVE/bundle.json","state":"https://pith.science/pith/VTLF2SF3LYPEGT7F7Z2FOZ2FVE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VTLF2SF3LYPEGT7F7Z2FOZ2FVE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:VTLF2SF3LYPEGT7F7Z2FOZ2FVE","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":"ec18ef8c797bc5d856fbbc85c81a3875b69f53ea2a23c262a8ecd6b0fbfa61c8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-17T06:49:29Z","title_canon_sha256":"864f856704878893925604125f4455b3ef7b5209da3201f95aed14dafdcfcbde"},"schema_version":"1.0","source":{"id":"2105.07637","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.07637","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"arxiv_version","alias_value":"2105.07637v2","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.07637","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"pith_short_12","alias_value":"VTLF2SF3LYPE","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"pith_short_16","alias_value":"VTLF2SF3LYPEGT7F","created_at":"2026-07-05T03:44:10Z"},{"alias_kind":"pith_short_8","alias_value":"VTLF2SF3","created_at":"2026-07-05T03:44:10Z"}],"graph_snapshots":[{"event_id":"sha256:892b4e7a0403e335ad309ea6f9e20f5441a3e135b3d7a0a0b9474df522c36841","target":"graph","created_at":"2026-07-05T03:44:10Z","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/2105.07637/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conventional detection networks usually need abundant labeled training samples, while humans can learn new concepts incrementally with just a few examples. This paper focuses on a more challenging but realistic class-incremental few-shot object detection problem (iFSD). It aims to incrementally transfer the model for novel objects from only a few annotated samples without catastrophically forgetting the previously learned ones. To tackle this problem, we propose a novel method LEAST, which can transfer with Less forgetting, fEwer training resources, And Stronger Transfer capability. Specifical","authors_text":"Donghui Wang, Han Cui, Pengyang Li, Yanan Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-17T06:49:29Z","title":"Class-Incremental Few-Shot Object Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.07637","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:b00ec4022d6b8e300d2c8e1957f1daf23df931fe43091f9c147c0f93894dca0b","target":"record","created_at":"2026-07-05T03:44:10Z","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":"ec18ef8c797bc5d856fbbc85c81a3875b69f53ea2a23c262a8ecd6b0fbfa61c8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-17T06:49:29Z","title_canon_sha256":"864f856704878893925604125f4455b3ef7b5209da3201f95aed14dafdcfcbde"},"schema_version":"1.0","source":{"id":"2105.07637","kind":"arxiv","version":2}},"canonical_sha256":"acd65d48bb5e1e434fe5fe74576745a921408b3dab4882307265d4e95d6c3a7e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"acd65d48bb5e1e434fe5fe74576745a921408b3dab4882307265d4e95d6c3a7e","first_computed_at":"2026-07-05T03:44:10.389401Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:44:10.389401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mYxguAXZzembvlBzT6LP1eH2iV+HRyrfQxXWBb1/MHFqtazk/UTlseVtU8WP5UIo+rRWRcHOW9mejL1xI1APCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:44:10.389859Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.07637","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b00ec4022d6b8e300d2c8e1957f1daf23df931fe43091f9c147c0f93894dca0b","sha256:892b4e7a0403e335ad309ea6f9e20f5441a3e135b3d7a0a0b9474df522c36841"],"state_sha256":"8b4516be5658ba07fb822cbc67476e20d18c6f3c1a1d2e5acdc36ddcc8f9bd1d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kUp4SRSUGIgHgMl3tFeHxAxWTGWgDTLrdGASmubBnaYb5PWuMmJAuPpDrOD0AoRS1A708VdFVw7A2/vV8yZuDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T02:37:14.275451Z","bundle_sha256":"81e2c8f2a47f01a081978842cace0f8a7a209c3bc76a9cfe7eb6b354aa7dbfaf"}}