{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:QOM237BIBZ5L5DXJH6IOYYYBNU","short_pith_number":"pith:QOM237BI","schema_version":"1.0","canonical_sha256":"8399adfc280e7abe8ee93f90ec63016d359838221916359bfb275758c581618a","source":{"kind":"arxiv","id":"1807.02480","version":2},"attestation_state":"computed","paper":{"title":"A Fully Convolutional Two-Stream Fusion Network for Interactive Image Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrea Soltoggio, Russell Lock, Steve Carter, Yang Hu","submitted_at":"2018-07-06T16:48:31Z","abstract_excerpt":"In this paper, we propose a novel fully convolutional two-stream fusion network (FCTSFN) for interactive image segmentation. The proposed network includes two sub-networks: a two-stream late fusion network (TSLFN) that predicts the foreground at a reduced resolution, and a multi-scale refining network (MSRN) that refines the foreground at full resolution. The TSLFN includes two distinct deep streams followed by a fusion network. The intuition is that, since user interactions are more direct information on foreground/background than the image itself, the two-stream structure of the TSLFN reduce"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1807.02480","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-06T16:48:31Z","cross_cats_sorted":[],"title_canon_sha256":"7fc8f72c60354ddfae1cbc26be8a488bada6491d30bb11f9d6bdc4b0945d0ae5","abstract_canon_sha256":"9192d071321f29bccf1bee1e5ef71cb799c3a4145bf14e3a67f2e116173aaabc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:12.733482Z","signature_b64":"g8uNo5Zl+YvbWJbZUK3aHXM09ICoK/gYaFHaZwcFVb9tO5eHO8wnv7G7ZoFucu/90Nc0y47cefkNsBfgXiT8Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8399adfc280e7abe8ee93f90ec63016d359838221916359bfb275758c581618a","last_reissued_at":"2026-05-18T00:04:12.732832Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:12.732832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Fully Convolutional Two-Stream Fusion Network for Interactive Image Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrea Soltoggio, Russell Lock, Steve Carter, Yang Hu","submitted_at":"2018-07-06T16:48:31Z","abstract_excerpt":"In this paper, we propose a novel fully convolutional two-stream fusion network (FCTSFN) for interactive image segmentation. The proposed network includes two sub-networks: a two-stream late fusion network (TSLFN) that predicts the foreground at a reduced resolution, and a multi-scale refining network (MSRN) that refines the foreground at full resolution. The TSLFN includes two distinct deep streams followed by a fusion network. The intuition is that, since user interactions are more direct information on foreground/background than the image itself, the two-stream structure of the TSLFN reduce"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.02480","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1807.02480","created_at":"2026-05-18T00:04:12.732922+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.02480v2","created_at":"2026-05-18T00:04:12.732922+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.02480","created_at":"2026-05-18T00:04:12.732922+00:00"},{"alias_kind":"pith_short_12","alias_value":"QOM237BIBZ5L","created_at":"2026-05-18T12:32:46.962924+00:00"},{"alias_kind":"pith_short_16","alias_value":"QOM237BIBZ5L5DXJ","created_at":"2026-05-18T12:32:46.962924+00:00"},{"alias_kind":"pith_short_8","alias_value":"QOM237BI","created_at":"2026-05-18T12:32:46.962924+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QOM237BIBZ5L5DXJH6IOYYYBNU","json":"https://pith.science/pith/QOM237BIBZ5L5DXJH6IOYYYBNU.json","graph_json":"https://pith.science/api/pith-number/QOM237BIBZ5L5DXJH6IOYYYBNU/graph.json","events_json":"https://pith.science/api/pith-number/QOM237BIBZ5L5DXJH6IOYYYBNU/events.json","paper":"https://pith.science/paper/QOM237BI"},"agent_actions":{"view_html":"https://pith.science/pith/QOM237BIBZ5L5DXJH6IOYYYBNU","download_json":"https://pith.science/pith/QOM237BIBZ5L5DXJH6IOYYYBNU.json","view_paper":"https://pith.science/paper/QOM237BI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.02480&json=true","fetch_graph":"https://pith.science/api/pith-number/QOM237BIBZ5L5DXJH6IOYYYBNU/graph.json","fetch_events":"https://pith.science/api/pith-number/QOM237BIBZ5L5DXJH6IOYYYBNU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QOM237BIBZ5L5DXJH6IOYYYBNU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QOM237BIBZ5L5DXJH6IOYYYBNU/action/storage_attestation","attest_author":"https://pith.science/pith/QOM237BIBZ5L5DXJH6IOYYYBNU/action/author_attestation","sign_citation":"https://pith.science/pith/QOM237BIBZ5L5DXJH6IOYYYBNU/action/citation_signature","submit_replication":"https://pith.science/pith/QOM237BIBZ5L5DXJH6IOYYYBNU/action/replication_record"}},"created_at":"2026-05-18T00:04:12.732922+00:00","updated_at":"2026-05-18T00:04:12.732922+00:00"}