{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:VA7JEGB5EHZ4QEKJVDUCPUU6B7","short_pith_number":"pith:VA7JEGB5","schema_version":"1.0","canonical_sha256":"a83e92183d21f3c81149a8e827d29e0fcb5856e16376f98b144492603ba82870","source":{"kind":"arxiv","id":"1904.07426","version":3},"attestation_state":"computed","paper":{"title":"Single Pixel Reconstruction for One-stage Instance Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dacheng Tao, Jian Zhang, Jinghan Yao, Jun Yu, Zhou Yu","submitted_at":"2019-04-16T03:11:13Z","abstract_excerpt":"Object instance segmentation is one of the most fundamental but challenging tasks in computer vision, and it requires the pixel-level image understanding. Most existing approaches address this problem by adding a mask prediction branch to a two-stage object detector with the Region Proposal Network (RPN). Although producing good segmentation results, the efficiency of these two-stage approaches is far from satisfactory, restricting their applicability in practice. In this paper, we propose a one-stage framework, SPRNet, which performs efficient instance segmentation by introducing a single pix"},"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":"1904.07426","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T03:11:13Z","cross_cats_sorted":[],"title_canon_sha256":"f1dfdbe4503b3d7ad1b75c60090e65d51c4e9a1570a6bdc5b21d0fcbc454c7d7","abstract_canon_sha256":"7a3ba5c7da2055ec25f2063768e281c773d7b37343102ecfbdf71792bbbe151e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:45:57.724766Z","signature_b64":"OilYhW2MPQVwRS4vlfzNTBJyHAVrJIl0Yzvt6fUmcu8wywRmRL0KMdwln6XZdtKcyFTJVBMWhc6Rm912a7riDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a83e92183d21f3c81149a8e827d29e0fcb5856e16376f98b144492603ba82870","last_reissued_at":"2026-05-17T23:45:57.724127Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:45:57.724127Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Single Pixel Reconstruction for One-stage Instance Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dacheng Tao, Jian Zhang, Jinghan Yao, Jun Yu, Zhou Yu","submitted_at":"2019-04-16T03:11:13Z","abstract_excerpt":"Object instance segmentation is one of the most fundamental but challenging tasks in computer vision, and it requires the pixel-level image understanding. Most existing approaches address this problem by adding a mask prediction branch to a two-stage object detector with the Region Proposal Network (RPN). Although producing good segmentation results, the efficiency of these two-stage approaches is far from satisfactory, restricting their applicability in practice. In this paper, we propose a one-stage framework, SPRNet, which performs efficient instance segmentation by introducing a single pix"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.07426","kind":"arxiv","version":3},"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":"1904.07426","created_at":"2026-05-17T23:45:57.724215+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.07426v3","created_at":"2026-05-17T23:45:57.724215+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.07426","created_at":"2026-05-17T23:45:57.724215+00:00"},{"alias_kind":"pith_short_12","alias_value":"VA7JEGB5EHZ4","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_16","alias_value":"VA7JEGB5EHZ4QEKJ","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_8","alias_value":"VA7JEGB5","created_at":"2026-05-18T12:33:30.264802+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/VA7JEGB5EHZ4QEKJVDUCPUU6B7","json":"https://pith.science/pith/VA7JEGB5EHZ4QEKJVDUCPUU6B7.json","graph_json":"https://pith.science/api/pith-number/VA7JEGB5EHZ4QEKJVDUCPUU6B7/graph.json","events_json":"https://pith.science/api/pith-number/VA7JEGB5EHZ4QEKJVDUCPUU6B7/events.json","paper":"https://pith.science/paper/VA7JEGB5"},"agent_actions":{"view_html":"https://pith.science/pith/VA7JEGB5EHZ4QEKJVDUCPUU6B7","download_json":"https://pith.science/pith/VA7JEGB5EHZ4QEKJVDUCPUU6B7.json","view_paper":"https://pith.science/paper/VA7JEGB5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.07426&json=true","fetch_graph":"https://pith.science/api/pith-number/VA7JEGB5EHZ4QEKJVDUCPUU6B7/graph.json","fetch_events":"https://pith.science/api/pith-number/VA7JEGB5EHZ4QEKJVDUCPUU6B7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VA7JEGB5EHZ4QEKJVDUCPUU6B7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VA7JEGB5EHZ4QEKJVDUCPUU6B7/action/storage_attestation","attest_author":"https://pith.science/pith/VA7JEGB5EHZ4QEKJVDUCPUU6B7/action/author_attestation","sign_citation":"https://pith.science/pith/VA7JEGB5EHZ4QEKJVDUCPUU6B7/action/citation_signature","submit_replication":"https://pith.science/pith/VA7JEGB5EHZ4QEKJVDUCPUU6B7/action/replication_record"}},"created_at":"2026-05-17T23:45:57.724215+00:00","updated_at":"2026-05-17T23:45:57.724215+00:00"}