{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:FIAWLGGWIWLOC5MFAT2FQR3MN3","short_pith_number":"pith:FIAWLGGW","canonical_record":{"source":{"id":"1811.00202","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-01T03:16:02Z","cross_cats_sorted":[],"title_canon_sha256":"6a21d3af6c8c3fd0b186f3bc1bba21a2e96bdb2b2158123e9c1304165cee5040","abstract_canon_sha256":"3efcf18667d88aa31eda9d618d307a62fd365eacd3ed7bc0e168442d9064285f"},"schema_version":"1.0"},"canonical_sha256":"2a016598d64596e1758504f458476c6ede1d9b631591aa808a9cf768f718ad51","source":{"kind":"arxiv","id":"1811.00202","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.00202","created_at":"2026-05-17T23:55:28Z"},{"alias_kind":"arxiv_version","alias_value":"1811.00202v2","created_at":"2026-05-17T23:55:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.00202","created_at":"2026-05-17T23:55:28Z"},{"alias_kind":"pith_short_12","alias_value":"FIAWLGGWIWLO","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FIAWLGGWIWLOC5MF","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FIAWLGGW","created_at":"2026-05-18T12:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:FIAWLGGWIWLOC5MFAT2FQR3MN3","target":"record","payload":{"canonical_record":{"source":{"id":"1811.00202","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-01T03:16:02Z","cross_cats_sorted":[],"title_canon_sha256":"6a21d3af6c8c3fd0b186f3bc1bba21a2e96bdb2b2158123e9c1304165cee5040","abstract_canon_sha256":"3efcf18667d88aa31eda9d618d307a62fd365eacd3ed7bc0e168442d9064285f"},"schema_version":"1.0"},"canonical_sha256":"2a016598d64596e1758504f458476c6ede1d9b631591aa808a9cf768f718ad51","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:28.754864Z","signature_b64":"UoX2P+tRN/Itre+wwu2MCAZEH3dw9khYaXIsJhe5iwWjd4oc347bcXH8aLcUDVhIFeGnX/tXrIAdaqz0c6SwBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2a016598d64596e1758504f458476c6ede1d9b631591aa808a9cf768f718ad51","last_reissued_at":"2026-05-17T23:55:28.754468Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:28.754468Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.00202","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":"2026-05-17T23:55:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K7DxERFrzmW0ccKAVIs+lV80/2c/PsYtg/ALLzAGJaRHAjz9YE+eYsW1unuq+67MB/9DGwXnYjUgm03ycUH+CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T13:51:36.494438Z"},"content_sha256":"1baece0023012bb9990d039f02c60234ceccadd51627fefcaa2c30320704a46e","schema_version":"1.0","event_id":"sha256:1baece0023012bb9990d039f02c60234ceccadd51627fefcaa2c30320704a46e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:FIAWLGGWIWLOC5MFAT2FQR3MN3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Attention-Aware Generalized Mean Pooling for Image Retrieval","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chuanpeng Li, Jinbin Xie, Yinzheng Gu","submitted_at":"2018-11-01T03:16:02Z","abstract_excerpt":"It has been shown that image descriptors extracted by convolutional neural networks (CNNs) achieve remarkable results for retrieval problems. In this paper, we apply attention mechanism to CNN, which aims at enhancing more relevant features that correspond to important keypoints in the input image. The generated attention-aware features are then aggregated by the previous state-of-the-art generalized mean (GeM) pooling followed by normalization to produce a compact global descriptor, which can be efficiently compared to other image descriptors by the dot product. An extensive comparison of our"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.00202","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":""},"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":"2026-05-17T23:55:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A7i9ik38pLf4srAqua3rbztEUaONYQbAPWb0lyewXnbO2y8IYkTJeAXQ/xciPZSEvWX/tyQiUQZV5pocobc6CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T13:51:36.494787Z"},"content_sha256":"bde769bf78c569546c72b19d5e122e2d9e3ea63f9b0c6e888508940a4105839e","schema_version":"1.0","event_id":"sha256:bde769bf78c569546c72b19d5e122e2d9e3ea63f9b0c6e888508940a4105839e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FIAWLGGWIWLOC5MFAT2FQR3MN3/bundle.json","state_url":"https://pith.science/pith/FIAWLGGWIWLOC5MFAT2FQR3MN3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FIAWLGGWIWLOC5MFAT2FQR3MN3/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":"2026-06-08T13:51:36Z","links":{"resolver":"https://pith.science/pith/FIAWLGGWIWLOC5MFAT2FQR3MN3","bundle":"https://pith.science/pith/FIAWLGGWIWLOC5MFAT2FQR3MN3/bundle.json","state":"https://pith.science/pith/FIAWLGGWIWLOC5MFAT2FQR3MN3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FIAWLGGWIWLOC5MFAT2FQR3MN3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:FIAWLGGWIWLOC5MFAT2FQR3MN3","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":"3efcf18667d88aa31eda9d618d307a62fd365eacd3ed7bc0e168442d9064285f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-01T03:16:02Z","title_canon_sha256":"6a21d3af6c8c3fd0b186f3bc1bba21a2e96bdb2b2158123e9c1304165cee5040"},"schema_version":"1.0","source":{"id":"1811.00202","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.00202","created_at":"2026-05-17T23:55:28Z"},{"alias_kind":"arxiv_version","alias_value":"1811.00202v2","created_at":"2026-05-17T23:55:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.00202","created_at":"2026-05-17T23:55:28Z"},{"alias_kind":"pith_short_12","alias_value":"FIAWLGGWIWLO","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FIAWLGGWIWLOC5MF","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FIAWLGGW","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:bde769bf78c569546c72b19d5e122e2d9e3ea63f9b0c6e888508940a4105839e","target":"graph","created_at":"2026-05-17T23:55:28Z","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":"It has been shown that image descriptors extracted by convolutional neural networks (CNNs) achieve remarkable results for retrieval problems. In this paper, we apply attention mechanism to CNN, which aims at enhancing more relevant features that correspond to important keypoints in the input image. The generated attention-aware features are then aggregated by the previous state-of-the-art generalized mean (GeM) pooling followed by normalization to produce a compact global descriptor, which can be efficiently compared to other image descriptors by the dot product. An extensive comparison of our","authors_text":"Chuanpeng Li, Jinbin Xie, Yinzheng Gu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-01T03:16:02Z","title":"Attention-Aware Generalized Mean Pooling for Image Retrieval"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.00202","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":"sha256:1baece0023012bb9990d039f02c60234ceccadd51627fefcaa2c30320704a46e","target":"record","created_at":"2026-05-17T23:55:28Z","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":"3efcf18667d88aa31eda9d618d307a62fd365eacd3ed7bc0e168442d9064285f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-01T03:16:02Z","title_canon_sha256":"6a21d3af6c8c3fd0b186f3bc1bba21a2e96bdb2b2158123e9c1304165cee5040"},"schema_version":"1.0","source":{"id":"1811.00202","kind":"arxiv","version":2}},"canonical_sha256":"2a016598d64596e1758504f458476c6ede1d9b631591aa808a9cf768f718ad51","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2a016598d64596e1758504f458476c6ede1d9b631591aa808a9cf768f718ad51","first_computed_at":"2026-05-17T23:55:28.754468Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:55:28.754468Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UoX2P+tRN/Itre+wwu2MCAZEH3dw9khYaXIsJhe5iwWjd4oc347bcXH8aLcUDVhIFeGnX/tXrIAdaqz0c6SwBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:55:28.754864Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.00202","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1baece0023012bb9990d039f02c60234ceccadd51627fefcaa2c30320704a46e","sha256:bde769bf78c569546c72b19d5e122e2d9e3ea63f9b0c6e888508940a4105839e"],"state_sha256":"a13e8f75ddaedd3acd17722dcfa42f865db71f35c4cff0d6f8eb27499d6f46a8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xC9BzDSXw7oP3ZAAtETTSz2v8b0pgvMGvetb3pWwQ8yWL7hiDGfMZXFRUf70BFOQ7N8oilahBOvp7G0d2z+eCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T13:51:36.496811Z","bundle_sha256":"7e001fbbfc4d616a0d1a87f987bbbbdaff62822cf475c5b41b167ad5c8d772ef"}}