{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:6WBVNVWSIYMOW27VCD34HTQCDH","short_pith_number":"pith:6WBVNVWS","canonical_record":{"source":{"id":"1707.02319","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-07T18:05:48Z","cross_cats_sorted":[],"title_canon_sha256":"e8a263667c5396669223135723bec2d78bbe32d93d6dbecf2a1d5d0381332aed","abstract_canon_sha256":"932aa2af60dac716a748675362be305eb624a05255fc35e674c7eedc4749ba1d"},"schema_version":"1.0"},"canonical_sha256":"f58356d6d24618eb6bf510f7c3ce0219e68ff32f457251e4e27e8d26b91890c9","source":{"kind":"arxiv","id":"1707.02319","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.02319","created_at":"2026-05-18T00:40:39Z"},{"alias_kind":"arxiv_version","alias_value":"1707.02319v1","created_at":"2026-05-18T00:40:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.02319","created_at":"2026-05-18T00:40:39Z"},{"alias_kind":"pith_short_12","alias_value":"6WBVNVWSIYMO","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"6WBVNVWSIYMOW27V","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"6WBVNVWS","created_at":"2026-05-18T12:31:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:6WBVNVWSIYMOW27VCD34HTQCDH","target":"record","payload":{"canonical_record":{"source":{"id":"1707.02319","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-07T18:05:48Z","cross_cats_sorted":[],"title_canon_sha256":"e8a263667c5396669223135723bec2d78bbe32d93d6dbecf2a1d5d0381332aed","abstract_canon_sha256":"932aa2af60dac716a748675362be305eb624a05255fc35e674c7eedc4749ba1d"},"schema_version":"1.0"},"canonical_sha256":"f58356d6d24618eb6bf510f7c3ce0219e68ff32f457251e4e27e8d26b91890c9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:40:39.539682Z","signature_b64":"JeYRzDWHWP4oHWVJdtkmAPynZQ/FRcqrehoqaJY3O/QNyiDqp9FltYMNHS1g+xt72q6vdrtjnO/xzV80f1csDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f58356d6d24618eb6bf510f7c3ce0219e68ff32f457251e4e27e8d26b91890c9","last_reissued_at":"2026-05-18T00:40:39.538983Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:40:39.538983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.02319","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":"2026-05-18T00:40:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"up2VXtVOBP5Xr2mOEYLC7eZyPcNMYfIkH36Cnl3FXJHPBPCTNyz0l3Q9i7v+4oapepfra/74FIl/bDL05e+aBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T23:20:15.928750Z"},"content_sha256":"2869daba9b71a090d687369073b8ca15b99140d6b9e6eb1d98bd1924b80082b1","schema_version":"1.0","event_id":"sha256:2869daba9b71a090d687369073b8ca15b99140d6b9e6eb1d98bd1924b80082b1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:6WBVNVWSIYMOW27VCD34HTQCDH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Efficient Image Representation for Person Re-Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Shengcai Liao, Stan Z. Li, Yang Yang, Zhen Lei","submitted_at":"2017-07-07T18:05:48Z","abstract_excerpt":"Color names based image representation is successfully used in person re-identification, due to the advantages of being compact, intuitively understandable as well as being robust to photometric variance. However, there exists the diversity between underlying distribution of color names' RGB values and that of image pixels' RGB values, which may lead to inaccuracy when directly comparing them in Euclidean space. In this paper, we propose a new method named soft Gaussian mapping (SGM) to address this problem. We model the discrepancies between color names and pixels using a Gaussian and utilize"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.02319","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":""},"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":"2026-05-18T00:40:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tcmWvmoQIHCivTjbV/XCLTcM46ypdPmdeWQtyg76UUQnTEYVmpJnnzlsOZBp4JOg8bQKWHamPK7pdVn6+gOyAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T23:20:15.929355Z"},"content_sha256":"939aab73b222493e06f9270821acf7b7e1ccb9fdc13a75248a78e2ae5306d775","schema_version":"1.0","event_id":"sha256:939aab73b222493e06f9270821acf7b7e1ccb9fdc13a75248a78e2ae5306d775"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6WBVNVWSIYMOW27VCD34HTQCDH/bundle.json","state_url":"https://pith.science/pith/6WBVNVWSIYMOW27VCD34HTQCDH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6WBVNVWSIYMOW27VCD34HTQCDH/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":"2026-06-04T23:20:15Z","links":{"resolver":"https://pith.science/pith/6WBVNVWSIYMOW27VCD34HTQCDH","bundle":"https://pith.science/pith/6WBVNVWSIYMOW27VCD34HTQCDH/bundle.json","state":"https://pith.science/pith/6WBVNVWSIYMOW27VCD34HTQCDH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6WBVNVWSIYMOW27VCD34HTQCDH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:6WBVNVWSIYMOW27VCD34HTQCDH","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":"932aa2af60dac716a748675362be305eb624a05255fc35e674c7eedc4749ba1d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-07T18:05:48Z","title_canon_sha256":"e8a263667c5396669223135723bec2d78bbe32d93d6dbecf2a1d5d0381332aed"},"schema_version":"1.0","source":{"id":"1707.02319","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.02319","created_at":"2026-05-18T00:40:39Z"},{"alias_kind":"arxiv_version","alias_value":"1707.02319v1","created_at":"2026-05-18T00:40:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.02319","created_at":"2026-05-18T00:40:39Z"},{"alias_kind":"pith_short_12","alias_value":"6WBVNVWSIYMO","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"6WBVNVWSIYMOW27V","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"6WBVNVWS","created_at":"2026-05-18T12:31:03Z"}],"graph_snapshots":[{"event_id":"sha256:939aab73b222493e06f9270821acf7b7e1ccb9fdc13a75248a78e2ae5306d775","target":"graph","created_at":"2026-05-18T00:40:39Z","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"},"paper":{"abstract_excerpt":"Color names based image representation is successfully used in person re-identification, due to the advantages of being compact, intuitively understandable as well as being robust to photometric variance. However, there exists the diversity between underlying distribution of color names' RGB values and that of image pixels' RGB values, which may lead to inaccuracy when directly comparing them in Euclidean space. In this paper, we propose a new method named soft Gaussian mapping (SGM) to address this problem. We model the discrepancies between color names and pixels using a Gaussian and utilize","authors_text":"Shengcai Liao, Stan Z. Li, Yang Yang, Zhen Lei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-07T18:05:48Z","title":"Learning Efficient Image Representation for Person Re-Identification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.02319","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":"sha256:2869daba9b71a090d687369073b8ca15b99140d6b9e6eb1d98bd1924b80082b1","target":"record","created_at":"2026-05-18T00:40:39Z","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":"932aa2af60dac716a748675362be305eb624a05255fc35e674c7eedc4749ba1d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-07T18:05:48Z","title_canon_sha256":"e8a263667c5396669223135723bec2d78bbe32d93d6dbecf2a1d5d0381332aed"},"schema_version":"1.0","source":{"id":"1707.02319","kind":"arxiv","version":1}},"canonical_sha256":"f58356d6d24618eb6bf510f7c3ce0219e68ff32f457251e4e27e8d26b91890c9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f58356d6d24618eb6bf510f7c3ce0219e68ff32f457251e4e27e8d26b91890c9","first_computed_at":"2026-05-18T00:40:39.538983Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:40:39.538983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JeYRzDWHWP4oHWVJdtkmAPynZQ/FRcqrehoqaJY3O/QNyiDqp9FltYMNHS1g+xt72q6vdrtjnO/xzV80f1csDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:40:39.539682Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.02319","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2869daba9b71a090d687369073b8ca15b99140d6b9e6eb1d98bd1924b80082b1","sha256:939aab73b222493e06f9270821acf7b7e1ccb9fdc13a75248a78e2ae5306d775"],"state_sha256":"1e5dd9039a74710a9005c518d129bd8c5e97da95fb1c54cd8d5e6b5dc08e531d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eh5WUAkRUCAkaUBfPuagxiU/QG1gQvjA1JYC2cPZpZVox2Q8jqyovuooJOM+eVO+8dO8kxzfNI7vGY44AKtlDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T23:20:15.932965Z","bundle_sha256":"f43990c834f949a82f238cd3f2e4452f34fa1098c0e6cd5ac5db091779856f9a"}}