{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:SIMEWSZFDH3MVBUQ3G7LGJL6PO","short_pith_number":"pith:SIMEWSZF","canonical_record":{"source":{"id":"1705.08923","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-24T18:36:58Z","cross_cats_sorted":[],"title_canon_sha256":"285c2bf1c25c4186668f80c4ddae426881b7b61146d3e0d95f432c92f97b7f8f","abstract_canon_sha256":"9c3b0525913c2860b4f87dda617dde9692f1ba1c408221fcc68e18ab72f831f4"},"schema_version":"1.0"},"canonical_sha256":"92184b4b2519f6ca8690d9beb3257e7bafa35569170000e226c9f9f135ded2b2","source":{"kind":"arxiv","id":"1705.08923","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.08923","created_at":"2026-05-18T00:43:42Z"},{"alias_kind":"arxiv_version","alias_value":"1705.08923v1","created_at":"2026-05-18T00:43:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.08923","created_at":"2026-05-18T00:43:42Z"},{"alias_kind":"pith_short_12","alias_value":"SIMEWSZFDH3M","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"SIMEWSZFDH3MVBUQ","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"SIMEWSZF","created_at":"2026-05-18T12:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:SIMEWSZFDH3MVBUQ3G7LGJL6PO","target":"record","payload":{"canonical_record":{"source":{"id":"1705.08923","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-24T18:36:58Z","cross_cats_sorted":[],"title_canon_sha256":"285c2bf1c25c4186668f80c4ddae426881b7b61146d3e0d95f432c92f97b7f8f","abstract_canon_sha256":"9c3b0525913c2860b4f87dda617dde9692f1ba1c408221fcc68e18ab72f831f4"},"schema_version":"1.0"},"canonical_sha256":"92184b4b2519f6ca8690d9beb3257e7bafa35569170000e226c9f9f135ded2b2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:43:42.941405Z","signature_b64":"ImD1vmjGFt5vC2wVuAXpFxl/hLw1pn6B4JWl93elJfxjIbmViz8AbjNLdKxNfaN5+rd4NfU9jpZaKXn/eotuAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92184b4b2519f6ca8690d9beb3257e7bafa35569170000e226c9f9f135ded2b2","last_reissued_at":"2026-05-18T00:43:42.940941Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:43:42.940941Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1705.08923","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":"2026-05-18T00:43:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kFge8N9jj8zSt0cBpi65yKtTUU8X+Vof2O0YMZhXYv6voVL34uf+SI4rzOfXUiBUzoE4rSzpxZHjM7H0rz1yBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T06:11:46.583624Z"},"content_sha256":"7962c4cf04ceacd0e2338011bc20749abff664f9210200517b30ee752b612b2e","schema_version":"1.0","event_id":"sha256:7962c4cf04ceacd0e2338011bc20749abff664f9210200517b30ee752b612b2e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:SIMEWSZFDH3MVBUQ3G7LGJL6PO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Attention-based Natural Language Person Retrieval","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Demetri Terzopoulos, Jie Yu, Muhao Chen, Tao Zhou","submitted_at":"2017-05-24T18:36:58Z","abstract_excerpt":"Following the recent progress in image classification and captioning using deep learning, we develop a novel natural language person retrieval system based on an attention mechanism. More specifically, given the description of a person, the goal is to localize the person in an image. To this end, we first construct a benchmark dataset for natural language person retrieval. To do so, we generate bounding boxes for persons in a public image dataset from the segmentation masks, which are then annotated with descriptions and attributes using the Amazon Mechanical Turk. We then adopt a region propo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.08923","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":"2026-05-18T00:43:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hzGg3aeAojFDIEXkzSOiqs6io2/lxhFpfVaRkO4cdmGWw8EVnPQ41E+377lzWRy7ZxQwZB3Ny0M2/V1sVCGsDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T06:11:46.584023Z"},"content_sha256":"26d951e33fc667e36ef4114d40aa199a01c2c8771fb830e6108b18991f417f9b","schema_version":"1.0","event_id":"sha256:26d951e33fc667e36ef4114d40aa199a01c2c8771fb830e6108b18991f417f9b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SIMEWSZFDH3MVBUQ3G7LGJL6PO/bundle.json","state_url":"https://pith.science/pith/SIMEWSZFDH3MVBUQ3G7LGJL6PO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SIMEWSZFDH3MVBUQ3G7LGJL6PO/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":"2026-05-30T06:11:46Z","links":{"resolver":"https://pith.science/pith/SIMEWSZFDH3MVBUQ3G7LGJL6PO","bundle":"https://pith.science/pith/SIMEWSZFDH3MVBUQ3G7LGJL6PO/bundle.json","state":"https://pith.science/pith/SIMEWSZFDH3MVBUQ3G7LGJL6PO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SIMEWSZFDH3MVBUQ3G7LGJL6PO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:SIMEWSZFDH3MVBUQ3G7LGJL6PO","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":"9c3b0525913c2860b4f87dda617dde9692f1ba1c408221fcc68e18ab72f831f4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-24T18:36:58Z","title_canon_sha256":"285c2bf1c25c4186668f80c4ddae426881b7b61146d3e0d95f432c92f97b7f8f"},"schema_version":"1.0","source":{"id":"1705.08923","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.08923","created_at":"2026-05-18T00:43:42Z"},{"alias_kind":"arxiv_version","alias_value":"1705.08923v1","created_at":"2026-05-18T00:43:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.08923","created_at":"2026-05-18T00:43:42Z"},{"alias_kind":"pith_short_12","alias_value":"SIMEWSZFDH3M","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"SIMEWSZFDH3MVBUQ","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"SIMEWSZF","created_at":"2026-05-18T12:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:26d951e33fc667e36ef4114d40aa199a01c2c8771fb830e6108b18991f417f9b","target":"graph","created_at":"2026-05-18T00:43:42Z","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":"Following the recent progress in image classification and captioning using deep learning, we develop a novel natural language person retrieval system based on an attention mechanism. More specifically, given the description of a person, the goal is to localize the person in an image. To this end, we first construct a benchmark dataset for natural language person retrieval. To do so, we generate bounding boxes for persons in a public image dataset from the segmentation masks, which are then annotated with descriptions and attributes using the Amazon Mechanical Turk. We then adopt a region propo","authors_text":"Demetri Terzopoulos, Jie Yu, Muhao Chen, Tao Zhou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-24T18:36:58Z","title":"Attention-based Natural Language Person Retrieval"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.08923","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":"sha256:7962c4cf04ceacd0e2338011bc20749abff664f9210200517b30ee752b612b2e","target":"record","created_at":"2026-05-18T00:43:42Z","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":"9c3b0525913c2860b4f87dda617dde9692f1ba1c408221fcc68e18ab72f831f4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-24T18:36:58Z","title_canon_sha256":"285c2bf1c25c4186668f80c4ddae426881b7b61146d3e0d95f432c92f97b7f8f"},"schema_version":"1.0","source":{"id":"1705.08923","kind":"arxiv","version":1}},"canonical_sha256":"92184b4b2519f6ca8690d9beb3257e7bafa35569170000e226c9f9f135ded2b2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"92184b4b2519f6ca8690d9beb3257e7bafa35569170000e226c9f9f135ded2b2","first_computed_at":"2026-05-18T00:43:42.940941Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:43:42.940941Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ImD1vmjGFt5vC2wVuAXpFxl/hLw1pn6B4JWl93elJfxjIbmViz8AbjNLdKxNfaN5+rd4NfU9jpZaKXn/eotuAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:43:42.941405Z","signed_message":"canonical_sha256_bytes"},"source_id":"1705.08923","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7962c4cf04ceacd0e2338011bc20749abff664f9210200517b30ee752b612b2e","sha256:26d951e33fc667e36ef4114d40aa199a01c2c8771fb830e6108b18991f417f9b"],"state_sha256":"50bae722b917b58bfea91b9099944e4c585363830b6221e3ea102d894da21a57"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x/lhZnyVlLdywQ0CfAmJSKP3DrEc+mw24V6DU5aLCk/aieJzR6wVTj0JXh8vcf8nd0BTCN/CZBoGdQETvFZLBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T06:11:46.585979Z","bundle_sha256":"d52b3c470b31d73e177d3ba3b225758027fe5ff1271a045eba529177d70a2b46"}}