{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:6C53JQLPCQXJIFOBP2NY4ZDYTY","short_pith_number":"pith:6C53JQLP","schema_version":"1.0","canonical_sha256":"f0bbb4c16f142e9415c17e9b8e64789e097de3bebb18fe353ec38b732dc648c7","source":{"kind":"arxiv","id":"2211.09375","version":1},"attestation_state":"computed","paper":{"title":"3D-QueryIS: A Query-based Framework for 3D Instance Segmentation","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hongcheng Guo, Honghui Yang, Jiaheng Liu, Jiayi Tian, Junran Wu, Ke Xu, Rui Su, Tong He, Wanli Ouyang","submitted_at":"2022-11-17T07:04:53Z","abstract_excerpt":"Previous top-performing methods for 3D instance segmentation often maintain inter-task dependencies and the tendency towards a lack of robustness. Besides, inevitable variations of different datasets make these methods become particularly sensitive to hyper-parameter values and manifest poor generalization capability. In this paper, we address the aforementioned challenges by proposing a novel query-based method, termed as 3D-QueryIS, which is detector-free, semantic segmentation-free, and cluster-free. Specifically, we propose to generate representative points in an implicit manner, and use t"},"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":"2211.09375","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2022-11-17T07:04:53Z","cross_cats_sorted":[],"title_canon_sha256":"d5263a9bf3ab9eab1afed5fb62df4f7a636bc666b4c38484e8ccda15e848ad53","abstract_canon_sha256":"54241bfa5db0ced1d1926c330f073a8f04a2f7e41a5b76bd11307183b3b66f7d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:16:55.179798Z","signature_b64":"djeHKPoP/dANi8DRcEzEAM0MTGC5isU4c0FxmLftFuCs6v8df2EgihSiyxrOkpSxvt/sCTMezkcld+Lj2SpvBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f0bbb4c16f142e9415c17e9b8e64789e097de3bebb18fe353ec38b732dc648c7","last_reissued_at":"2026-07-05T05:16:55.179390Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:16:55.179390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"3D-QueryIS: A Query-based Framework for 3D Instance Segmentation","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hongcheng Guo, Honghui Yang, Jiaheng Liu, Jiayi Tian, Junran Wu, Ke Xu, Rui Su, Tong He, Wanli Ouyang","submitted_at":"2022-11-17T07:04:53Z","abstract_excerpt":"Previous top-performing methods for 3D instance segmentation often maintain inter-task dependencies and the tendency towards a lack of robustness. Besides, inevitable variations of different datasets make these methods become particularly sensitive to hyper-parameter values and manifest poor generalization capability. In this paper, we address the aforementioned challenges by proposing a novel query-based method, termed as 3D-QueryIS, which is detector-free, semantic segmentation-free, and cluster-free. Specifically, we propose to generate representative points in an implicit manner, and use t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.09375","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2211.09375/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":"2211.09375","created_at":"2026-07-05T05:16:55.179446+00:00"},{"alias_kind":"arxiv_version","alias_value":"2211.09375v1","created_at":"2026-07-05T05:16:55.179446+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.09375","created_at":"2026-07-05T05:16:55.179446+00:00"},{"alias_kind":"pith_short_12","alias_value":"6C53JQLPCQXJ","created_at":"2026-07-05T05:16:55.179446+00:00"},{"alias_kind":"pith_short_16","alias_value":"6C53JQLPCQXJIFOB","created_at":"2026-07-05T05:16:55.179446+00:00"},{"alias_kind":"pith_short_8","alias_value":"6C53JQLP","created_at":"2026-07-05T05:16:55.179446+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/6C53JQLPCQXJIFOBP2NY4ZDYTY","json":"https://pith.science/pith/6C53JQLPCQXJIFOBP2NY4ZDYTY.json","graph_json":"https://pith.science/api/pith-number/6C53JQLPCQXJIFOBP2NY4ZDYTY/graph.json","events_json":"https://pith.science/api/pith-number/6C53JQLPCQXJIFOBP2NY4ZDYTY/events.json","paper":"https://pith.science/paper/6C53JQLP"},"agent_actions":{"view_html":"https://pith.science/pith/6C53JQLPCQXJIFOBP2NY4ZDYTY","download_json":"https://pith.science/pith/6C53JQLPCQXJIFOBP2NY4ZDYTY.json","view_paper":"https://pith.science/paper/6C53JQLP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2211.09375&json=true","fetch_graph":"https://pith.science/api/pith-number/6C53JQLPCQXJIFOBP2NY4ZDYTY/graph.json","fetch_events":"https://pith.science/api/pith-number/6C53JQLPCQXJIFOBP2NY4ZDYTY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6C53JQLPCQXJIFOBP2NY4ZDYTY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6C53JQLPCQXJIFOBP2NY4ZDYTY/action/storage_attestation","attest_author":"https://pith.science/pith/6C53JQLPCQXJIFOBP2NY4ZDYTY/action/author_attestation","sign_citation":"https://pith.science/pith/6C53JQLPCQXJIFOBP2NY4ZDYTY/action/citation_signature","submit_replication":"https://pith.science/pith/6C53JQLPCQXJIFOBP2NY4ZDYTY/action/replication_record"}},"created_at":"2026-07-05T05:16:55.179446+00:00","updated_at":"2026-07-05T05:16:55.179446+00:00"}