{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:RII65YWPXCQBPNEML7ECRJEWZR","short_pith_number":"pith:RII65YWP","schema_version":"1.0","canonical_sha256":"8a11eee2cfb8a017b48c5fc828a496cc6e364e72a4bb55b897495a25481c3aee","source":{"kind":"arxiv","id":"2209.15215","version":2},"attestation_state":"computed","paper":{"title":"INT: Towards Infinite-frames 3D Detection with An Efficient Framework","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Da Zhang, Hongmin Li, Hongyu Pan, Jianyun Xu, Jun Zhu, Kaixuan Liu, Peihan Hao, Xin Zhan, Zhengyang Sun, Zhenwei Miao","submitted_at":"2022-09-30T04:03:40Z","abstract_excerpt":"It is natural to construct a multi-frame instead of a single-frame 3D detector for a continuous-time stream. Although increasing the number of frames might improve performance, previous multi-frame studies only used very limited frames to build their systems due to the dramatically increased computational and memory cost. To address these issues, we propose a novel on-stream training and prediction framework that, in theory, can employ an infinite number of frames while keeping the same amount of computation as a single-frame detector. This infinite framework (INT), which can be used with most"},"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":"2209.15215","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2022-09-30T04:03:40Z","cross_cats_sorted":[],"title_canon_sha256":"481240c0359f3e5f2ee11f1a4450469b6408122461ad13d9cd3418ffe2eda5c5","abstract_canon_sha256":"b99e3f3d31fece251260fc7701cfa622e381362ba9cf97c39f2033c44dfd4d93"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:40:49.678108Z","signature_b64":"R722xXls76uirAyCaTgGjJc3JQ5Ch2CtjpNKR6Enk4iyTwupOuEqM+bD3R0ShftOtep9kPgKUPffbNEVJdoACw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8a11eee2cfb8a017b48c5fc828a496cc6e364e72a4bb55b897495a25481c3aee","last_reissued_at":"2026-07-05T05:40:49.677592Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:40:49.677592Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"INT: Towards Infinite-frames 3D Detection with An Efficient Framework","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Da Zhang, Hongmin Li, Hongyu Pan, Jianyun Xu, Jun Zhu, Kaixuan Liu, Peihan Hao, Xin Zhan, Zhengyang Sun, Zhenwei Miao","submitted_at":"2022-09-30T04:03:40Z","abstract_excerpt":"It is natural to construct a multi-frame instead of a single-frame 3D detector for a continuous-time stream. Although increasing the number of frames might improve performance, previous multi-frame studies only used very limited frames to build their systems due to the dramatically increased computational and memory cost. To address these issues, we propose a novel on-stream training and prediction framework that, in theory, can employ an infinite number of frames while keeping the same amount of computation as a single-frame detector. This infinite framework (INT), which can be used with most"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.15215","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/2209.15215/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":"2209.15215","created_at":"2026-07-05T05:40:49.677657+00:00"},{"alias_kind":"arxiv_version","alias_value":"2209.15215v2","created_at":"2026-07-05T05:40:49.677657+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.15215","created_at":"2026-07-05T05:40:49.677657+00:00"},{"alias_kind":"pith_short_12","alias_value":"RII65YWPXCQB","created_at":"2026-07-05T05:40:49.677657+00:00"},{"alias_kind":"pith_short_16","alias_value":"RII65YWPXCQBPNEM","created_at":"2026-07-05T05:40:49.677657+00:00"},{"alias_kind":"pith_short_8","alias_value":"RII65YWP","created_at":"2026-07-05T05:40:49.677657+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/RII65YWPXCQBPNEML7ECRJEWZR","json":"https://pith.science/pith/RII65YWPXCQBPNEML7ECRJEWZR.json","graph_json":"https://pith.science/api/pith-number/RII65YWPXCQBPNEML7ECRJEWZR/graph.json","events_json":"https://pith.science/api/pith-number/RII65YWPXCQBPNEML7ECRJEWZR/events.json","paper":"https://pith.science/paper/RII65YWP"},"agent_actions":{"view_html":"https://pith.science/pith/RII65YWPXCQBPNEML7ECRJEWZR","download_json":"https://pith.science/pith/RII65YWPXCQBPNEML7ECRJEWZR.json","view_paper":"https://pith.science/paper/RII65YWP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2209.15215&json=true","fetch_graph":"https://pith.science/api/pith-number/RII65YWPXCQBPNEML7ECRJEWZR/graph.json","fetch_events":"https://pith.science/api/pith-number/RII65YWPXCQBPNEML7ECRJEWZR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RII65YWPXCQBPNEML7ECRJEWZR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RII65YWPXCQBPNEML7ECRJEWZR/action/storage_attestation","attest_author":"https://pith.science/pith/RII65YWPXCQBPNEML7ECRJEWZR/action/author_attestation","sign_citation":"https://pith.science/pith/RII65YWPXCQBPNEML7ECRJEWZR/action/citation_signature","submit_replication":"https://pith.science/pith/RII65YWPXCQBPNEML7ECRJEWZR/action/replication_record"}},"created_at":"2026-07-05T05:40:49.677657+00:00","updated_at":"2026-07-05T05:40:49.677657+00:00"}