{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:6YI4N6P52OLIT46TACCKIEWT6V","short_pith_number":"pith:6YI4N6P5","canonical_record":{"source":{"id":"2103.05918","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-10T08:19:46Z","cross_cats_sorted":[],"title_canon_sha256":"f8c38958bab03f7efcbda65b1ede6303fbe3009d8bd6988071b8a2b2fd4ab7a8","abstract_canon_sha256":"ac9f9fe419de0e674d0d730c12c0de674798c56f343ca8689591c292e7f3da51"},"schema_version":"1.0"},"canonical_sha256":"f611c6f9fdd39689f3d30084a412d3f54760be9169c7b7cc3c9fe3963746e758","source":{"kind":"arxiv","id":"2103.05918","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.05918","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"arxiv_version","alias_value":"2103.05918v1","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.05918","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"pith_short_12","alias_value":"6YI4N6P52OLI","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"pith_short_16","alias_value":"6YI4N6P52OLIT46T","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"pith_short_8","alias_value":"6YI4N6P5","created_at":"2026-07-05T02:21:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:6YI4N6P52OLIT46TACCKIEWT6V","target":"record","payload":{"canonical_record":{"source":{"id":"2103.05918","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-10T08:19:46Z","cross_cats_sorted":[],"title_canon_sha256":"f8c38958bab03f7efcbda65b1ede6303fbe3009d8bd6988071b8a2b2fd4ab7a8","abstract_canon_sha256":"ac9f9fe419de0e674d0d730c12c0de674798c56f343ca8689591c292e7f3da51"},"schema_version":"1.0"},"canonical_sha256":"f611c6f9fdd39689f3d30084a412d3f54760be9169c7b7cc3c9fe3963746e758","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:21:59.545438Z","signature_b64":"ngBijiqAM6dxOqXx6V0mciG3clmHAISVQnGghzDn1/5OubpyRxxDgSYGpX56Xb8NdSm/OqTBMGPXSaxaQ6jcAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f611c6f9fdd39689f3d30084a412d3f54760be9169c7b7cc3c9fe3963746e758","last_reissued_at":"2026-07-05T02:21:59.545006Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:21:59.545006Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2103.05918","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":"2026-07-05T02:21:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"psljk5kDgWGHW5mnAi8EhAT/jKTni4hB71EUIpmnN6nBh2zzMXWXsv+qI3vwTKoLAOSS6TFdy6CBtE1CMpb6Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T04:31:06.781568Z"},"content_sha256":"466faaf951238299befd557a2656f4bd11d6bcc664c6af1b805bb30331022a57","schema_version":"1.0","event_id":"sha256:466faaf951238299befd557a2656f4bd11d6bcc664c6af1b805bb30331022a57"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:6YI4N6P52OLIT46TACCKIEWT6V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ES-Net: Erasing Salient Parts to Learn More in Re-Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Deng Cai, Dong Shen, Hao Feng, Jinming Hu, Shuai Zhao, Xiaofei He","submitted_at":"2021-03-10T08:19:46Z","abstract_excerpt":"As an instance-level recognition problem, re-identification (re-ID) requires models to capture diverse features. However, with continuous training, re-ID models pay more and more attention to the salient areas. As a result, the model may only focus on few small regions with salient representations and ignore other important information. This phenomenon leads to inferior performance, especially when models are evaluated on small inter-identity variation data. In this paper, we propose a novel network, Erasing-Salient Net (ES-Net), to learn comprehensive features by erasing the salient areas in "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.05918","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/2103.05918/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":"2026-07-05T02:21:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dr7niqOakPDvtgf/R2cuQ2zKLtY0RMmWqc+spQVr/nUbt6LdoEayzPd6o+0/gukEpxwxsWKownAGly88+gzyAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T04:31:06.782034Z"},"content_sha256":"9bac4f3c4994760a5b9d99cd139cb7ed63293191d23db525435816aeb90b6cf4","schema_version":"1.0","event_id":"sha256:9bac4f3c4994760a5b9d99cd139cb7ed63293191d23db525435816aeb90b6cf4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6YI4N6P52OLIT46TACCKIEWT6V/bundle.json","state_url":"https://pith.science/pith/6YI4N6P52OLIT46TACCKIEWT6V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6YI4N6P52OLIT46TACCKIEWT6V/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":"2026-08-06T04:31:06Z","links":{"resolver":"https://pith.science/pith/6YI4N6P52OLIT46TACCKIEWT6V","bundle":"https://pith.science/pith/6YI4N6P52OLIT46TACCKIEWT6V/bundle.json","state":"https://pith.science/pith/6YI4N6P52OLIT46TACCKIEWT6V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6YI4N6P52OLIT46TACCKIEWT6V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:6YI4N6P52OLIT46TACCKIEWT6V","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":"ac9f9fe419de0e674d0d730c12c0de674798c56f343ca8689591c292e7f3da51","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-10T08:19:46Z","title_canon_sha256":"f8c38958bab03f7efcbda65b1ede6303fbe3009d8bd6988071b8a2b2fd4ab7a8"},"schema_version":"1.0","source":{"id":"2103.05918","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.05918","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"arxiv_version","alias_value":"2103.05918v1","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.05918","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"pith_short_12","alias_value":"6YI4N6P52OLI","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"pith_short_16","alias_value":"6YI4N6P52OLIT46T","created_at":"2026-07-05T02:21:59Z"},{"alias_kind":"pith_short_8","alias_value":"6YI4N6P5","created_at":"2026-07-05T02:21:59Z"}],"graph_snapshots":[{"event_id":"sha256:9bac4f3c4994760a5b9d99cd139cb7ed63293191d23db525435816aeb90b6cf4","target":"graph","created_at":"2026-07-05T02:21:59Z","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/2103.05918/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As an instance-level recognition problem, re-identification (re-ID) requires models to capture diverse features. However, with continuous training, re-ID models pay more and more attention to the salient areas. As a result, the model may only focus on few small regions with salient representations and ignore other important information. This phenomenon leads to inferior performance, especially when models are evaluated on small inter-identity variation data. In this paper, we propose a novel network, Erasing-Salient Net (ES-Net), to learn comprehensive features by erasing the salient areas in ","authors_text":"Deng Cai, Dong Shen, Hao Feng, Jinming Hu, Shuai Zhao, Xiaofei He","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-10T08:19:46Z","title":"ES-Net: Erasing Salient Parts to Learn More in Re-Identification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.05918","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":"sha256:466faaf951238299befd557a2656f4bd11d6bcc664c6af1b805bb30331022a57","target":"record","created_at":"2026-07-05T02:21:59Z","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":"ac9f9fe419de0e674d0d730c12c0de674798c56f343ca8689591c292e7f3da51","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-03-10T08:19:46Z","title_canon_sha256":"f8c38958bab03f7efcbda65b1ede6303fbe3009d8bd6988071b8a2b2fd4ab7a8"},"schema_version":"1.0","source":{"id":"2103.05918","kind":"arxiv","version":1}},"canonical_sha256":"f611c6f9fdd39689f3d30084a412d3f54760be9169c7b7cc3c9fe3963746e758","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f611c6f9fdd39689f3d30084a412d3f54760be9169c7b7cc3c9fe3963746e758","first_computed_at":"2026-07-05T02:21:59.545006Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:21:59.545006Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ngBijiqAM6dxOqXx6V0mciG3clmHAISVQnGghzDn1/5OubpyRxxDgSYGpX56Xb8NdSm/OqTBMGPXSaxaQ6jcAw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:21:59.545438Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.05918","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:466faaf951238299befd557a2656f4bd11d6bcc664c6af1b805bb30331022a57","sha256:9bac4f3c4994760a5b9d99cd139cb7ed63293191d23db525435816aeb90b6cf4"],"state_sha256":"fb67108fd7791f57107f473a6c3bad671f24039323b39688fc798140d29fcc67"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9SNIjjTJ8LqD7h1aNiSCLDaeA81BZ90V94OuJguKY18a0rUMErzEdpQA7ylny/9eDUjcIBNYqwOEl30318SxBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T04:31:06.785631Z","bundle_sha256":"a6d9081986850bae7a4e2141b5195bbbfb689b9ea6be927862b90550e617ab04"}}