{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:JUQAVBIAIU6MXGKFN5DJOEANZ4","short_pith_number":"pith:JUQAVBIA","schema_version":"1.0","canonical_sha256":"4d200a8500453ccb99456f4697100dcf0054e72927e5542f6a491d58a53a1175","source":{"kind":"arxiv","id":"2009.13342","version":2},"attestation_state":"computed","paper":{"title":"Learning Category- and Instance-Aware Pixel Embedding for Fast Panoptic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kaiqi Huang, Naiyu Gao, Xin Zhao, Yanhu Shan","submitted_at":"2020-09-28T14:07:50Z","abstract_excerpt":"Panoptic segmentation (PS) is a complex scene understanding task that requires providing high-quality segmentation for both thing objects and stuff regions. Previous methods handle these two classes with semantic and instance segmentation modules separately, following with heuristic fusion or additional modules to resolve the conflicts between the two outputs. This work simplifies this pipeline of PS by consistently modeling the two classes with a novel PS framework, which extends a detection model with an extra module to predict category- and instance-aware pixel embedding (CIAE). CIAE is a n"},"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":"2009.13342","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-09-28T14:07:50Z","cross_cats_sorted":[],"title_canon_sha256":"21152bb376737d9ffea9abff3a6ca0bf0bda501eaba836edc0c7a3a9ba5b0f3d","abstract_canon_sha256":"6fb5ee81ec1f27700b6a99e5a152032b713b8b1c4c13b68903673c255dcc7d7f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:52:57.853669Z","signature_b64":"tYb4h8KALEN9KZqAcf6Bo/O8Qd/bSMFUBI5DmoZ4aKPHLQJZb2h2tKkEcvFR5ZOdjbHOcup1w+SGlGBIMe2SCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d200a8500453ccb99456f4697100dcf0054e72927e5542f6a491d58a53a1175","last_reissued_at":"2026-07-05T02:52:57.853261Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:52:57.853261Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning Category- and Instance-Aware Pixel Embedding for Fast Panoptic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kaiqi Huang, Naiyu Gao, Xin Zhao, Yanhu Shan","submitted_at":"2020-09-28T14:07:50Z","abstract_excerpt":"Panoptic segmentation (PS) is a complex scene understanding task that requires providing high-quality segmentation for both thing objects and stuff regions. Previous methods handle these two classes with semantic and instance segmentation modules separately, following with heuristic fusion or additional modules to resolve the conflicts between the two outputs. This work simplifies this pipeline of PS by consistently modeling the two classes with a novel PS framework, which extends a detection model with an extra module to predict category- and instance-aware pixel embedding (CIAE). CIAE is a n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.13342","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2009.13342/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2009.13342","created_at":"2026-07-05T02:52:57.853321+00:00"},{"alias_kind":"arxiv_version","alias_value":"2009.13342v2","created_at":"2026-07-05T02:52:57.853321+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.13342","created_at":"2026-07-05T02:52:57.853321+00:00"},{"alias_kind":"pith_short_12","alias_value":"JUQAVBIAIU6M","created_at":"2026-07-05T02:52:57.853321+00:00"},{"alias_kind":"pith_short_16","alias_value":"JUQAVBIAIU6MXGKF","created_at":"2026-07-05T02:52:57.853321+00:00"},{"alias_kind":"pith_short_8","alias_value":"JUQAVBIA","created_at":"2026-07-05T02:52:57.853321+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/JUQAVBIAIU6MXGKFN5DJOEANZ4","json":"https://pith.science/pith/JUQAVBIAIU6MXGKFN5DJOEANZ4.json","graph_json":"https://pith.science/api/pith-number/JUQAVBIAIU6MXGKFN5DJOEANZ4/graph.json","events_json":"https://pith.science/api/pith-number/JUQAVBIAIU6MXGKFN5DJOEANZ4/events.json","paper":"https://pith.science/paper/JUQAVBIA"},"agent_actions":{"view_html":"https://pith.science/pith/JUQAVBIAIU6MXGKFN5DJOEANZ4","download_json":"https://pith.science/pith/JUQAVBIAIU6MXGKFN5DJOEANZ4.json","view_paper":"https://pith.science/paper/JUQAVBIA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2009.13342&json=true","fetch_graph":"https://pith.science/api/pith-number/JUQAVBIAIU6MXGKFN5DJOEANZ4/graph.json","fetch_events":"https://pith.science/api/pith-number/JUQAVBIAIU6MXGKFN5DJOEANZ4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JUQAVBIAIU6MXGKFN5DJOEANZ4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JUQAVBIAIU6MXGKFN5DJOEANZ4/action/storage_attestation","attest_author":"https://pith.science/pith/JUQAVBIAIU6MXGKFN5DJOEANZ4/action/author_attestation","sign_citation":"https://pith.science/pith/JUQAVBIAIU6MXGKFN5DJOEANZ4/action/citation_signature","submit_replication":"https://pith.science/pith/JUQAVBIAIU6MXGKFN5DJOEANZ4/action/replication_record"}},"created_at":"2026-07-05T02:52:57.853321+00:00","updated_at":"2026-07-05T02:52:57.853321+00:00"}