{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:ENDBR7EMWPXVCD5QHBMRCZVPQT","short_pith_number":"pith:ENDBR7EM","schema_version":"1.0","canonical_sha256":"234618fc8cb3ef510fb038591166af84ceaccc193b323604b7abedaed73ee3f8","source":{"kind":"arxiv","id":"2304.04442","version":1},"attestation_state":"computed","paper":{"title":"Monte Carlo Linear Clustering with Single-Point Supervision is Enough for Infrared Small Target Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Boyang Li, Fei Zhang, Longguang Wang, Ting Liu, Wei An, Yingqian Wang, Yulan Guo, Zaiping Lin","submitted_at":"2023-04-10T08:04:05Z","abstract_excerpt":"Single-frame infrared small target (SIRST) detection aims at separating small targets from clutter backgrounds on infrared images. Recently, deep learning based methods have achieved promising performance on SIRST detection, but at the cost of a large amount of training data with expensive pixel-level annotations. To reduce the annotation burden, we propose the first method to achieve SIRST detection with single-point supervision. The core idea of this work is to recover the per-pixel mask of each target from the given single point label by using clustering approaches, which looks simple but i"},"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":"2304.04442","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-10T08:04:05Z","cross_cats_sorted":[],"title_canon_sha256":"403a714a6004efdd0dbf21b2609192fc64a0283cde79397fb7a794d272f238e7","abstract_canon_sha256":"5a076e3c628dc110bd3eac9455cbe65cbb57729bb57247bf6127699753f8b31b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:59:26.266713Z","signature_b64":"BNEYP/KsKhB+I8FB66uPp1BMLRbbLyBfVoRmNNjbAgu882NIc6RIMmTjxv9bkwyQHOV3B7KtDfvintZ1MGtxDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"234618fc8cb3ef510fb038591166af84ceaccc193b323604b7abedaed73ee3f8","last_reissued_at":"2026-07-05T05:59:26.266290Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:59:26.266290Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Monte Carlo Linear Clustering with Single-Point Supervision is Enough for Infrared Small Target Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Boyang Li, Fei Zhang, Longguang Wang, Ting Liu, Wei An, Yingqian Wang, Yulan Guo, Zaiping Lin","submitted_at":"2023-04-10T08:04:05Z","abstract_excerpt":"Single-frame infrared small target (SIRST) detection aims at separating small targets from clutter backgrounds on infrared images. Recently, deep learning based methods have achieved promising performance on SIRST detection, but at the cost of a large amount of training data with expensive pixel-level annotations. To reduce the annotation burden, we propose the first method to achieve SIRST detection with single-point supervision. The core idea of this work is to recover the per-pixel mask of each target from the given single point label by using clustering approaches, which looks simple but i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.04442","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/2304.04442/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":"2304.04442","created_at":"2026-07-05T05:59:26.266361+00:00"},{"alias_kind":"arxiv_version","alias_value":"2304.04442v1","created_at":"2026-07-05T05:59:26.266361+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.04442","created_at":"2026-07-05T05:59:26.266361+00:00"},{"alias_kind":"pith_short_12","alias_value":"ENDBR7EMWPXV","created_at":"2026-07-05T05:59:26.266361+00:00"},{"alias_kind":"pith_short_16","alias_value":"ENDBR7EMWPXVCD5Q","created_at":"2026-07-05T05:59:26.266361+00:00"},{"alias_kind":"pith_short_8","alias_value":"ENDBR7EM","created_at":"2026-07-05T05:59:26.266361+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/ENDBR7EMWPXVCD5QHBMRCZVPQT","json":"https://pith.science/pith/ENDBR7EMWPXVCD5QHBMRCZVPQT.json","graph_json":"https://pith.science/api/pith-number/ENDBR7EMWPXVCD5QHBMRCZVPQT/graph.json","events_json":"https://pith.science/api/pith-number/ENDBR7EMWPXVCD5QHBMRCZVPQT/events.json","paper":"https://pith.science/paper/ENDBR7EM"},"agent_actions":{"view_html":"https://pith.science/pith/ENDBR7EMWPXVCD5QHBMRCZVPQT","download_json":"https://pith.science/pith/ENDBR7EMWPXVCD5QHBMRCZVPQT.json","view_paper":"https://pith.science/paper/ENDBR7EM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2304.04442&json=true","fetch_graph":"https://pith.science/api/pith-number/ENDBR7EMWPXVCD5QHBMRCZVPQT/graph.json","fetch_events":"https://pith.science/api/pith-number/ENDBR7EMWPXVCD5QHBMRCZVPQT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ENDBR7EMWPXVCD5QHBMRCZVPQT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ENDBR7EMWPXVCD5QHBMRCZVPQT/action/storage_attestation","attest_author":"https://pith.science/pith/ENDBR7EMWPXVCD5QHBMRCZVPQT/action/author_attestation","sign_citation":"https://pith.science/pith/ENDBR7EMWPXVCD5QHBMRCZVPQT/action/citation_signature","submit_replication":"https://pith.science/pith/ENDBR7EMWPXVCD5QHBMRCZVPQT/action/replication_record"}},"created_at":"2026-07-05T05:59:26.266361+00:00","updated_at":"2026-07-05T05:59:26.266361+00:00"}