{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:5GXIMTJMWOA2LLROLMSRDKFPRH","short_pith_number":"pith:5GXIMTJM","canonical_record":{"source":{"id":"1711.10795","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T11:46:56Z","cross_cats_sorted":["cs.AI","cs.IR"],"title_canon_sha256":"6b8f595c3bf43ceb82f2c76183aa5f4a0ee68fff17303d76dbd7dc2701cf501c","abstract_canon_sha256":"864f716daf5814a969e88b59a83e17c51f8fa5c4eb81086c666576828a2fc2d5"},"schema_version":"1.0"},"canonical_sha256":"e9ae864d2cb381a5ae2e5b2511a8af89dd04899651badeac80885964103f9cac","source":{"kind":"arxiv","id":"1711.10795","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.10795","created_at":"2026-05-18T00:29:16Z"},{"alias_kind":"arxiv_version","alias_value":"1711.10795v1","created_at":"2026-05-18T00:29:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.10795","created_at":"2026-05-18T00:29:16Z"},{"alias_kind":"pith_short_12","alias_value":"5GXIMTJMWOA2","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"5GXIMTJMWOA2LLRO","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"5GXIMTJM","created_at":"2026-05-18T12:31:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:5GXIMTJMWOA2LLROLMSRDKFPRH","target":"record","payload":{"canonical_record":{"source":{"id":"1711.10795","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T11:46:56Z","cross_cats_sorted":["cs.AI","cs.IR"],"title_canon_sha256":"6b8f595c3bf43ceb82f2c76183aa5f4a0ee68fff17303d76dbd7dc2701cf501c","abstract_canon_sha256":"864f716daf5814a969e88b59a83e17c51f8fa5c4eb81086c666576828a2fc2d5"},"schema_version":"1.0"},"canonical_sha256":"e9ae864d2cb381a5ae2e5b2511a8af89dd04899651badeac80885964103f9cac","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:16.912264Z","signature_b64":"AFdtz8CfXbQRe8hWYKyEu4iDjasEyojlIki13KPJrigqHxMhpDyxpj41wVvUWUSsx3xBIFtmN59Zay6oNOlQBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e9ae864d2cb381a5ae2e5b2511a8af89dd04899651badeac80885964103f9cac","last_reissued_at":"2026-05-18T00:29:16.911808Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:16.911808Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.10795","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":"2026-05-18T00:29:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oho8S6/x+X9l4qk3e6Axi/Xrs023WSfYfcQXAmdHYhJx1pNzdYqpD1o8N+lxumYNPTNqBDm+m8aEPLjL5ZaADQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T06:04:48.979479Z"},"content_sha256":"6911bfed78a97d4e7906d67f973269559b9e605347ab05d2299f59aa9c26a872","schema_version":"1.0","event_id":"sha256:6911bfed78a97d4e7906d67f973269559b9e605347ab05d2299f59aa9c26a872"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:5GXIMTJMWOA2LLROLMSRDKFPRH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Saliency Weighted Convolutional Features for Instance Search","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.IR"],"primary_cat":"cs.CV","authors_text":"Eva Mohedano, Kevin McGuinness, Noel E. O'Connor, Xavier Giro-i-Nieto","submitted_at":"2017-11-29T11:46:56Z","abstract_excerpt":"This work explores attention models to weight the contribution of local convolutional representations for the instance search task. We present a retrieval framework based on bags of local convolutional features (BLCF) that benefits from saliency weighting to build an efficient image representation. The use of human visual attention models (saliency) allows significant improvements in retrieval performance without the need to conduct region analysis or spatial verification, and without requiring any feature fine tuning. We investigate the impact of different saliency models, finding that higher"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.10795","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":"2026-05-18T00:29:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lb8WoHEoI11WC2ttoEuYQD5ghWOnPHq8xvsj/ku6fakASXtnG2goAdzybWRpM4BJ+QOEJYgbDhzrS/fhLguxDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T06:04:48.979832Z"},"content_sha256":"117d41b78f2c70e15effd0935ef896510cc4655810872fbedb3024330f7889ec","schema_version":"1.0","event_id":"sha256:117d41b78f2c70e15effd0935ef896510cc4655810872fbedb3024330f7889ec"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5GXIMTJMWOA2LLROLMSRDKFPRH/bundle.json","state_url":"https://pith.science/pith/5GXIMTJMWOA2LLROLMSRDKFPRH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5GXIMTJMWOA2LLROLMSRDKFPRH/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":"2026-05-30T06:04:48Z","links":{"resolver":"https://pith.science/pith/5GXIMTJMWOA2LLROLMSRDKFPRH","bundle":"https://pith.science/pith/5GXIMTJMWOA2LLROLMSRDKFPRH/bundle.json","state":"https://pith.science/pith/5GXIMTJMWOA2LLROLMSRDKFPRH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5GXIMTJMWOA2LLROLMSRDKFPRH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:5GXIMTJMWOA2LLROLMSRDKFPRH","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":"864f716daf5814a969e88b59a83e17c51f8fa5c4eb81086c666576828a2fc2d5","cross_cats_sorted":["cs.AI","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T11:46:56Z","title_canon_sha256":"6b8f595c3bf43ceb82f2c76183aa5f4a0ee68fff17303d76dbd7dc2701cf501c"},"schema_version":"1.0","source":{"id":"1711.10795","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.10795","created_at":"2026-05-18T00:29:16Z"},{"alias_kind":"arxiv_version","alias_value":"1711.10795v1","created_at":"2026-05-18T00:29:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.10795","created_at":"2026-05-18T00:29:16Z"},{"alias_kind":"pith_short_12","alias_value":"5GXIMTJMWOA2","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"5GXIMTJMWOA2LLRO","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"5GXIMTJM","created_at":"2026-05-18T12:31:00Z"}],"graph_snapshots":[{"event_id":"sha256:117d41b78f2c70e15effd0935ef896510cc4655810872fbedb3024330f7889ec","target":"graph","created_at":"2026-05-18T00:29:16Z","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":"This work explores attention models to weight the contribution of local convolutional representations for the instance search task. We present a retrieval framework based on bags of local convolutional features (BLCF) that benefits from saliency weighting to build an efficient image representation. The use of human visual attention models (saliency) allows significant improvements in retrieval performance without the need to conduct region analysis or spatial verification, and without requiring any feature fine tuning. We investigate the impact of different saliency models, finding that higher","authors_text":"Eva Mohedano, Kevin McGuinness, Noel E. O'Connor, Xavier Giro-i-Nieto","cross_cats":["cs.AI","cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T11:46:56Z","title":"Saliency Weighted Convolutional Features for Instance Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.10795","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":"sha256:6911bfed78a97d4e7906d67f973269559b9e605347ab05d2299f59aa9c26a872","target":"record","created_at":"2026-05-18T00:29:16Z","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":"864f716daf5814a969e88b59a83e17c51f8fa5c4eb81086c666576828a2fc2d5","cross_cats_sorted":["cs.AI","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-29T11:46:56Z","title_canon_sha256":"6b8f595c3bf43ceb82f2c76183aa5f4a0ee68fff17303d76dbd7dc2701cf501c"},"schema_version":"1.0","source":{"id":"1711.10795","kind":"arxiv","version":1}},"canonical_sha256":"e9ae864d2cb381a5ae2e5b2511a8af89dd04899651badeac80885964103f9cac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e9ae864d2cb381a5ae2e5b2511a8af89dd04899651badeac80885964103f9cac","first_computed_at":"2026-05-18T00:29:16.911808Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:16.911808Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AFdtz8CfXbQRe8hWYKyEu4iDjasEyojlIki13KPJrigqHxMhpDyxpj41wVvUWUSsx3xBIFtmN59Zay6oNOlQBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:16.912264Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.10795","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6911bfed78a97d4e7906d67f973269559b9e605347ab05d2299f59aa9c26a872","sha256:117d41b78f2c70e15effd0935ef896510cc4655810872fbedb3024330f7889ec"],"state_sha256":"c4853745085c240072d5970b73043a471a0647c3902643381182ee79e827077e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"boOOEuNPe4wm4Uj9fJgbvUyUwEo4K1uGbkdZxgxZ3XTL7B1JKCsJxbKOo5thxtghp/l/a3BT0mUUEngyKB0KAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T06:04:48.981877Z","bundle_sha256":"da34f1d772f1ddd99a5376930f62e7575c0778299c950f139171a7c2acbd5b75"}}