{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:UVJVO7UZZYN4TSDZQJFNUGMET4","short_pith_number":"pith:UVJVO7UZ","canonical_record":{"source":{"id":"2110.15074","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-28T12:51:08Z","cross_cats_sorted":[],"title_canon_sha256":"26e2313d35e4e6ed8f095ad2f6a1df32c6df1aa5650d8ae6b79ec5474b970fdd","abstract_canon_sha256":"c9c3039bcc8ae7d082f1cae9ec40fd54ef34f96e53650e4960e5994f00140aa4"},"schema_version":"1.0"},"canonical_sha256":"a553577e99ce1bc9c879824ada19849f38e736183c5d00733c132da5bcbf48ab","source":{"kind":"arxiv","id":"2110.15074","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.15074","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"arxiv_version","alias_value":"2110.15074v1","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.15074","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"pith_short_12","alias_value":"UVJVO7UZZYN4","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"pith_short_16","alias_value":"UVJVO7UZZYN4TSDZ","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"pith_short_8","alias_value":"UVJVO7UZ","created_at":"2026-07-05T03:26:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:UVJVO7UZZYN4TSDZQJFNUGMET4","target":"record","payload":{"canonical_record":{"source":{"id":"2110.15074","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-28T12:51:08Z","cross_cats_sorted":[],"title_canon_sha256":"26e2313d35e4e6ed8f095ad2f6a1df32c6df1aa5650d8ae6b79ec5474b970fdd","abstract_canon_sha256":"c9c3039bcc8ae7d082f1cae9ec40fd54ef34f96e53650e4960e5994f00140aa4"},"schema_version":"1.0"},"canonical_sha256":"a553577e99ce1bc9c879824ada19849f38e736183c5d00733c132da5bcbf48ab","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:26:51.295929Z","signature_b64":"FgrHq2pFgjBZwdwZ/mixJUanpFaFt0lUNRl46fof/A2XtQV6gneEYoGMe89RawKvSIuXNQXXyLl91ZEijewSCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a553577e99ce1bc9c879824ada19849f38e736183c5d00733c132da5bcbf48ab","last_reissued_at":"2026-07-05T03:26:51.295477Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:26:51.295477Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.15074","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":"2026-07-05T03:26:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ejEJ27BhHtaf42fOEoPIxTpo3ObiBEcYqnZKnZiNkUUL/OYVomxKQcCdNfUL5jzZUaCTxv9hp7Z1EIq4Y8meCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-15T21:25:37.923376Z"},"content_sha256":"225d34b6f8beb2aa87e9b4b92c7221d35a91d05468e4c0e60505918ebcee24b9","schema_version":"1.0","event_id":"sha256:225d34b6f8beb2aa87e9b4b92c7221d35a91d05468e4c0e60505918ebcee24b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:UVJVO7UZZYN4TSDZQJFNUGMET4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Meta Guided Metric Learner for Overcoming Class Confusion in Few-Shot Road Object Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anay Majee, Anbumani Subramanian, Kshitij Agrawal","submitted_at":"2021-10-28T12:51:08Z","abstract_excerpt":"Localization and recognition of less-occurring road objects have been a challenge in autonomous driving applications due to the scarcity of data samples. Few-Shot Object Detection techniques extend the knowledge from existing base object classes to learn novel road objects given few training examples. Popular techniques in FSOD adopt either meta or metric learning techniques which are prone to class confusion and base class forgetting. In this work, we introduce a novel Meta Guided Metric Learner (MGML) to overcome class confusion in FSOD. We re-weight the features of the novel classes higher "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.15074","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/2110.15074/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":"2026-07-05T03:26:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aQ07PSojhg8C7vPMF3ntQJR3HevzZCu+Jz9iAl+i0hBGFxVe9ouCnA14CG5GUxoGEGbReddvRLmSjkoSCvtyDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-15T21:25:37.923751Z"},"content_sha256":"4b11189a74abe3e90c111fcfe00dbd4ebfac94c5b112092e366d715b49fc494a","schema_version":"1.0","event_id":"sha256:4b11189a74abe3e90c111fcfe00dbd4ebfac94c5b112092e366d715b49fc494a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UVJVO7UZZYN4TSDZQJFNUGMET4/bundle.json","state_url":"https://pith.science/pith/UVJVO7UZZYN4TSDZQJFNUGMET4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UVJVO7UZZYN4TSDZQJFNUGMET4/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":"2026-07-15T21:25:37Z","links":{"resolver":"https://pith.science/pith/UVJVO7UZZYN4TSDZQJFNUGMET4","bundle":"https://pith.science/pith/UVJVO7UZZYN4TSDZQJFNUGMET4/bundle.json","state":"https://pith.science/pith/UVJVO7UZZYN4TSDZQJFNUGMET4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UVJVO7UZZYN4TSDZQJFNUGMET4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:UVJVO7UZZYN4TSDZQJFNUGMET4","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":"c9c3039bcc8ae7d082f1cae9ec40fd54ef34f96e53650e4960e5994f00140aa4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-28T12:51:08Z","title_canon_sha256":"26e2313d35e4e6ed8f095ad2f6a1df32c6df1aa5650d8ae6b79ec5474b970fdd"},"schema_version":"1.0","source":{"id":"2110.15074","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.15074","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"arxiv_version","alias_value":"2110.15074v1","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.15074","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"pith_short_12","alias_value":"UVJVO7UZZYN4","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"pith_short_16","alias_value":"UVJVO7UZZYN4TSDZ","created_at":"2026-07-05T03:26:51Z"},{"alias_kind":"pith_short_8","alias_value":"UVJVO7UZ","created_at":"2026-07-05T03:26:51Z"}],"graph_snapshots":[{"event_id":"sha256:4b11189a74abe3e90c111fcfe00dbd4ebfac94c5b112092e366d715b49fc494a","target":"graph","created_at":"2026-07-05T03:26:51Z","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/2110.15074/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Localization and recognition of less-occurring road objects have been a challenge in autonomous driving applications due to the scarcity of data samples. Few-Shot Object Detection techniques extend the knowledge from existing base object classes to learn novel road objects given few training examples. Popular techniques in FSOD adopt either meta or metric learning techniques which are prone to class confusion and base class forgetting. In this work, we introduce a novel Meta Guided Metric Learner (MGML) to overcome class confusion in FSOD. We re-weight the features of the novel classes higher ","authors_text":"Anay Majee, Anbumani Subramanian, Kshitij Agrawal","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-28T12:51:08Z","title":"Meta Guided Metric Learner for Overcoming Class Confusion in Few-Shot Road Object Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.15074","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":"sha256:225d34b6f8beb2aa87e9b4b92c7221d35a91d05468e4c0e60505918ebcee24b9","target":"record","created_at":"2026-07-05T03:26:51Z","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":"c9c3039bcc8ae7d082f1cae9ec40fd54ef34f96e53650e4960e5994f00140aa4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-10-28T12:51:08Z","title_canon_sha256":"26e2313d35e4e6ed8f095ad2f6a1df32c6df1aa5650d8ae6b79ec5474b970fdd"},"schema_version":"1.0","source":{"id":"2110.15074","kind":"arxiv","version":1}},"canonical_sha256":"a553577e99ce1bc9c879824ada19849f38e736183c5d00733c132da5bcbf48ab","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a553577e99ce1bc9c879824ada19849f38e736183c5d00733c132da5bcbf48ab","first_computed_at":"2026-07-05T03:26:51.295477Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:26:51.295477Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FgrHq2pFgjBZwdwZ/mixJUanpFaFt0lUNRl46fof/A2XtQV6gneEYoGMe89RawKvSIuXNQXXyLl91ZEijewSCA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:26:51.295929Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.15074","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:225d34b6f8beb2aa87e9b4b92c7221d35a91d05468e4c0e60505918ebcee24b9","sha256:4b11189a74abe3e90c111fcfe00dbd4ebfac94c5b112092e366d715b49fc494a"],"state_sha256":"878e00a81c4e68d755b44922a38c8ab85c015e279ab393ac0ea8ffa431ff614c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4KkSQW5ZmaUCEEqPIw3jULQVtTDG6yXFGDN0VHJD9rJPOLMqruCJUMoy/PpSvMbLLIFzdJ7N6/tFjdNPQfyXBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-15T21:25:37.926407Z","bundle_sha256":"ddafe899c2cc6daea21fdb7cb8ecb45555de85fafbaa23a81f29a399e54d3245"}}