{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:C6UTH6ATCGV4FHQYR5GVAX7DFU","short_pith_number":"pith:C6UTH6AT","canonical_record":{"source":{"id":"1510.02927","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-10-10T13:36:31Z","cross_cats_sorted":[],"title_canon_sha256":"eeb9832be69e5dab45511dd5bbc5daf58d825df3b18c926f62d1db836d33ed5b","abstract_canon_sha256":"e83c98e1fbf8f0ad85eb886b2d4b3e9a3166d7dc62e278165bbf3c3f7f821898"},"schema_version":"1.0"},"canonical_sha256":"17a933f81311abc29e188f4d505fe32d1ec8ea84e9deb7e5d25568f695705a5c","source":{"kind":"arxiv","id":"1510.02927","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1510.02927","created_at":"2026-05-18T01:30:33Z"},{"alias_kind":"arxiv_version","alias_value":"1510.02927v1","created_at":"2026-05-18T01:30:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.02927","created_at":"2026-05-18T01:30:33Z"},{"alias_kind":"pith_short_12","alias_value":"C6UTH6ATCGV4","created_at":"2026-05-18T12:29:14Z"},{"alias_kind":"pith_short_16","alias_value":"C6UTH6ATCGV4FHQY","created_at":"2026-05-18T12:29:14Z"},{"alias_kind":"pith_short_8","alias_value":"C6UTH6AT","created_at":"2026-05-18T12:29:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:C6UTH6ATCGV4FHQYR5GVAX7DFU","target":"record","payload":{"canonical_record":{"source":{"id":"1510.02927","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-10-10T13:36:31Z","cross_cats_sorted":[],"title_canon_sha256":"eeb9832be69e5dab45511dd5bbc5daf58d825df3b18c926f62d1db836d33ed5b","abstract_canon_sha256":"e83c98e1fbf8f0ad85eb886b2d4b3e9a3166d7dc62e278165bbf3c3f7f821898"},"schema_version":"1.0"},"canonical_sha256":"17a933f81311abc29e188f4d505fe32d1ec8ea84e9deb7e5d25568f695705a5c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:30:33.328709Z","signature_b64":"E/go0hdPKIj8sDFjVhFFeW2KAMAai/qJBTRgeiRL6kKIHgjCo6YQ4Ask2j7oE8pGmFMdulFl4Oua/K8aAXf2BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17a933f81311abc29e188f4d505fe32d1ec8ea84e9deb7e5d25568f695705a5c","last_reissued_at":"2026-05-18T01:30:33.328078Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:30:33.328078Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1510.02927","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":"2026-05-18T01:30:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C7ckrhKeZ4APlpJZ8x01ebjCAOqqpdRl2ulZ3xxF3QgckABFSg8l5MsUmDJ0LpZW/V8mfo6gZ47TQ+87XMLXDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T12:06:49.270086Z"},"content_sha256":"6b469db1f0cb501ab338e5613b75566b0116f814667a7a91cc29a2e36f638e45","schema_version":"1.0","event_id":"sha256:6b469db1f0cb501ab338e5613b75566b0116f814667a7a91cc29a2e36f638e45"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:C6UTH6ATCGV4FHQYR5GVAX7DFU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepFix: A Fully Convolutional Neural Network for predicting Human Eye Fixations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kumar Ayush, R. Venkatesh Babu, Srinivas S. S. Kruthiventi","submitted_at":"2015-10-10T13:36:31Z","abstract_excerpt":"Understanding and predicting the human visual attentional mechanism is an active area of research in the fields of neuroscience and computer vision. In this work, we propose DeepFix, a first-of-its-kind fully convolutional neural network for accurate saliency prediction. Unlike classical works which characterize the saliency map using various hand-crafted features, our model automatically learns features in a hierarchical fashion and predicts saliency map in an end-to-end manner. DeepFix is designed to capture semantics at multiple scales while taking global context into account using network "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.02927","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":"2026-05-18T01:30:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ICQhKgbBGRqOw6wQS5gUKN7Al/X73DXpLnlbpQT/WA3rS/gyQv+Oi1sKk+6mMQCUPlgYqG7S9kEni6/3pt6OCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T12:06:49.270448Z"},"content_sha256":"6ccc7ba85cb3b6f64c402c28c734ef05caa192af185fbdcfb7e2bf342d636805","schema_version":"1.0","event_id":"sha256:6ccc7ba85cb3b6f64c402c28c734ef05caa192af185fbdcfb7e2bf342d636805"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C6UTH6ATCGV4FHQYR5GVAX7DFU/bundle.json","state_url":"https://pith.science/pith/C6UTH6ATCGV4FHQYR5GVAX7DFU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C6UTH6ATCGV4FHQYR5GVAX7DFU/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":"2026-06-30T12:06:49Z","links":{"resolver":"https://pith.science/pith/C6UTH6ATCGV4FHQYR5GVAX7DFU","bundle":"https://pith.science/pith/C6UTH6ATCGV4FHQYR5GVAX7DFU/bundle.json","state":"https://pith.science/pith/C6UTH6ATCGV4FHQYR5GVAX7DFU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C6UTH6ATCGV4FHQYR5GVAX7DFU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:C6UTH6ATCGV4FHQYR5GVAX7DFU","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":"e83c98e1fbf8f0ad85eb886b2d4b3e9a3166d7dc62e278165bbf3c3f7f821898","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-10-10T13:36:31Z","title_canon_sha256":"eeb9832be69e5dab45511dd5bbc5daf58d825df3b18c926f62d1db836d33ed5b"},"schema_version":"1.0","source":{"id":"1510.02927","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1510.02927","created_at":"2026-05-18T01:30:33Z"},{"alias_kind":"arxiv_version","alias_value":"1510.02927v1","created_at":"2026-05-18T01:30:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.02927","created_at":"2026-05-18T01:30:33Z"},{"alias_kind":"pith_short_12","alias_value":"C6UTH6ATCGV4","created_at":"2026-05-18T12:29:14Z"},{"alias_kind":"pith_short_16","alias_value":"C6UTH6ATCGV4FHQY","created_at":"2026-05-18T12:29:14Z"},{"alias_kind":"pith_short_8","alias_value":"C6UTH6AT","created_at":"2026-05-18T12:29:14Z"}],"graph_snapshots":[{"event_id":"sha256:6ccc7ba85cb3b6f64c402c28c734ef05caa192af185fbdcfb7e2bf342d636805","target":"graph","created_at":"2026-05-18T01:30:33Z","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":"Understanding and predicting the human visual attentional mechanism is an active area of research in the fields of neuroscience and computer vision. In this work, we propose DeepFix, a first-of-its-kind fully convolutional neural network for accurate saliency prediction. Unlike classical works which characterize the saliency map using various hand-crafted features, our model automatically learns features in a hierarchical fashion and predicts saliency map in an end-to-end manner. DeepFix is designed to capture semantics at multiple scales while taking global context into account using network ","authors_text":"Kumar Ayush, R. Venkatesh Babu, Srinivas S. S. Kruthiventi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-10-10T13:36:31Z","title":"DeepFix: A Fully Convolutional Neural Network for predicting Human Eye Fixations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.02927","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":"sha256:6b469db1f0cb501ab338e5613b75566b0116f814667a7a91cc29a2e36f638e45","target":"record","created_at":"2026-05-18T01:30:33Z","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":"e83c98e1fbf8f0ad85eb886b2d4b3e9a3166d7dc62e278165bbf3c3f7f821898","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-10-10T13:36:31Z","title_canon_sha256":"eeb9832be69e5dab45511dd5bbc5daf58d825df3b18c926f62d1db836d33ed5b"},"schema_version":"1.0","source":{"id":"1510.02927","kind":"arxiv","version":1}},"canonical_sha256":"17a933f81311abc29e188f4d505fe32d1ec8ea84e9deb7e5d25568f695705a5c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"17a933f81311abc29e188f4d505fe32d1ec8ea84e9deb7e5d25568f695705a5c","first_computed_at":"2026-05-18T01:30:33.328078Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:30:33.328078Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"E/go0hdPKIj8sDFjVhFFeW2KAMAai/qJBTRgeiRL6kKIHgjCo6YQ4Ask2j7oE8pGmFMdulFl4Oua/K8aAXf2BQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:30:33.328709Z","signed_message":"canonical_sha256_bytes"},"source_id":"1510.02927","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6b469db1f0cb501ab338e5613b75566b0116f814667a7a91cc29a2e36f638e45","sha256:6ccc7ba85cb3b6f64c402c28c734ef05caa192af185fbdcfb7e2bf342d636805"],"state_sha256":"06bf324161b8f93cf2f555f3411a4ba322ead9e321fdc5b4a3088a823006bace"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0sI2+pzNRbpqgwO3eB+5mDrjh5+0y9kwE6vJEYEBxw/gSA0Nqo0JdaYcBI+6QhT9S4mgedd5QVp/sEtekBsHCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T12:06:49.272294Z","bundle_sha256":"d05df9f78adb5cdf93d97c04259715879936f4928c7e87fc658f62d4e69279a6"}}