{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:ANXQ5MK4BQN35M3CI37RWLSL6N","short_pith_number":"pith:ANXQ5MK4","canonical_record":{"source":{"id":"1808.04702","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T21:53:22Z","cross_cats_sorted":[],"title_canon_sha256":"46c64fb1919383e76f9aa924167112bbdb1e54b4dcc7f1a20e304e012e7a10e5","abstract_canon_sha256":"afd03632b067a51c8c585a8b690772ffbc9c682be022b536b41f7d00785917cb"},"schema_version":"1.0"},"canonical_sha256":"036f0eb15c0c1bbeb36246ff1b2e4bf371441cb43ac5699409682d7405d23f6d","source":{"kind":"arxiv","id":"1808.04702","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.04702","created_at":"2026-05-17T23:58:08Z"},{"alias_kind":"arxiv_version","alias_value":"1808.04702v2","created_at":"2026-05-17T23:58:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.04702","created_at":"2026-05-17T23:58:08Z"},{"alias_kind":"pith_short_12","alias_value":"ANXQ5MK4BQN3","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"ANXQ5MK4BQN35M3C","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"ANXQ5MK4","created_at":"2026-05-18T12:32:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:ANXQ5MK4BQN35M3CI37RWLSL6N","target":"record","payload":{"canonical_record":{"source":{"id":"1808.04702","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T21:53:22Z","cross_cats_sorted":[],"title_canon_sha256":"46c64fb1919383e76f9aa924167112bbdb1e54b4dcc7f1a20e304e012e7a10e5","abstract_canon_sha256":"afd03632b067a51c8c585a8b690772ffbc9c682be022b536b41f7d00785917cb"},"schema_version":"1.0"},"canonical_sha256":"036f0eb15c0c1bbeb36246ff1b2e4bf371441cb43ac5699409682d7405d23f6d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:58:08.497685Z","signature_b64":"Sos87znMQPYRLiQCNIn0OIv/zNcbi26nf65AOivf3ErQ+9Sd5BkiSXFh++c1As3M0X5UfcqRH9V1+4+Kk1JxBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"036f0eb15c0c1bbeb36246ff1b2e4bf371441cb43ac5699409682d7405d23f6d","last_reissued_at":"2026-05-17T23:58:08.497140Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:58:08.497140Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.04702","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":"2026-05-17T23:58:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pyH76+LKaMTd+qsYmgEKiNEVp+UgiTcBXqr5g5atmIWgevkJMoE2ojbNzAVsL/PdgooTM/DrtHD8LhTMAVQTDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:01:36.494390Z"},"content_sha256":"c0e6ab83d47d1bcf0204abe23063dbca767d3125a8f306a6c939866b1be0d92e","schema_version":"1.0","event_id":"sha256:c0e6ab83d47d1bcf0204abe23063dbca767d3125a8f306a6c939866b1be0d92e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:ANXQ5MK4BQN35M3CI37RWLSL6N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bo Xiong, Kristen Grauman, Suyog Dutt Jain","submitted_at":"2018-08-11T21:53:22Z","abstract_excerpt":"We propose an end-to-end learning framework for segmenting generic objects in both images and videos. Given a novel image or video, our approach produces a pixel-level mask for all \"object-like\" regions---even for object categories never seen during training. We formulate the task as a structured prediction problem of assigning an object/background label to each pixel, implemented using a deep fully convolutional network. When applied to a video, our model further incorporates a motion stream, and the network learns to combine both appearance and motion and attempts to extract all prominent ob"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.04702","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":"2026-05-17T23:58:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xg54uGTUNy0eERmR3b/b7ICwDwXWaukufhWCUtIlDaqdYcIBsMypsCPQWNf7Uj981Zt1eHqiT9g+MI70mBWnDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:01:36.494747Z"},"content_sha256":"182a52f131b7361a4f91bcdfe78f6743065d7fa05868f8f157251810409cd932","schema_version":"1.0","event_id":"sha256:182a52f131b7361a4f91bcdfe78f6743065d7fa05868f8f157251810409cd932"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ANXQ5MK4BQN35M3CI37RWLSL6N/bundle.json","state_url":"https://pith.science/pith/ANXQ5MK4BQN35M3CI37RWLSL6N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ANXQ5MK4BQN35M3CI37RWLSL6N/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":"2026-08-04T10:01:36Z","links":{"resolver":"https://pith.science/pith/ANXQ5MK4BQN35M3CI37RWLSL6N","bundle":"https://pith.science/pith/ANXQ5MK4BQN35M3CI37RWLSL6N/bundle.json","state":"https://pith.science/pith/ANXQ5MK4BQN35M3CI37RWLSL6N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ANXQ5MK4BQN35M3CI37RWLSL6N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:ANXQ5MK4BQN35M3CI37RWLSL6N","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":"afd03632b067a51c8c585a8b690772ffbc9c682be022b536b41f7d00785917cb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T21:53:22Z","title_canon_sha256":"46c64fb1919383e76f9aa924167112bbdb1e54b4dcc7f1a20e304e012e7a10e5"},"schema_version":"1.0","source":{"id":"1808.04702","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.04702","created_at":"2026-05-17T23:58:08Z"},{"alias_kind":"arxiv_version","alias_value":"1808.04702v2","created_at":"2026-05-17T23:58:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.04702","created_at":"2026-05-17T23:58:08Z"},{"alias_kind":"pith_short_12","alias_value":"ANXQ5MK4BQN3","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"ANXQ5MK4BQN35M3C","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"ANXQ5MK4","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:182a52f131b7361a4f91bcdfe78f6743065d7fa05868f8f157251810409cd932","target":"graph","created_at":"2026-05-17T23:58:08Z","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":"We propose an end-to-end learning framework for segmenting generic objects in both images and videos. Given a novel image or video, our approach produces a pixel-level mask for all \"object-like\" regions---even for object categories never seen during training. We formulate the task as a structured prediction problem of assigning an object/background label to each pixel, implemented using a deep fully convolutional network. When applied to a video, our model further incorporates a motion stream, and the network learns to combine both appearance and motion and attempts to extract all prominent ob","authors_text":"Bo Xiong, Kristen Grauman, Suyog Dutt Jain","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T21:53:22Z","title":"Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.04702","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:c0e6ab83d47d1bcf0204abe23063dbca767d3125a8f306a6c939866b1be0d92e","target":"record","created_at":"2026-05-17T23:58:08Z","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":"afd03632b067a51c8c585a8b690772ffbc9c682be022b536b41f7d00785917cb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-11T21:53:22Z","title_canon_sha256":"46c64fb1919383e76f9aa924167112bbdb1e54b4dcc7f1a20e304e012e7a10e5"},"schema_version":"1.0","source":{"id":"1808.04702","kind":"arxiv","version":2}},"canonical_sha256":"036f0eb15c0c1bbeb36246ff1b2e4bf371441cb43ac5699409682d7405d23f6d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"036f0eb15c0c1bbeb36246ff1b2e4bf371441cb43ac5699409682d7405d23f6d","first_computed_at":"2026-05-17T23:58:08.497140Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:58:08.497140Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Sos87znMQPYRLiQCNIn0OIv/zNcbi26nf65AOivf3ErQ+9Sd5BkiSXFh++c1As3M0X5UfcqRH9V1+4+Kk1JxBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:58:08.497685Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.04702","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c0e6ab83d47d1bcf0204abe23063dbca767d3125a8f306a6c939866b1be0d92e","sha256:182a52f131b7361a4f91bcdfe78f6743065d7fa05868f8f157251810409cd932"],"state_sha256":"e30012658b72aac8828eaea0bbbe92d0293755615cc50d93512497c7275f780f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wlR7g7XyGJZw2XmaD7tm12EgsncWi0+Ft70EEoh9InfaVC247uO1QOK3a+9QwocUnSdIC/V6RlCIvvZAcNj8Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T10:01:36.497427Z","bundle_sha256":"c2f595ecc97b170d9b5b519f6b04e1dd2fce36ac4b99f94d181b079c54bf59cb"}}