{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:PM4PYAWQ22ZOTJWIP7I6QWL2UL","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"6e405f5addb0efbbafc35400c1103c7661b02cc455849616f72c42e9a86823aa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-07T23:10:40Z","title_canon_sha256":"90f79cba72d0045f99f58fe515488e3dcf4353cee8744498022fcb1ca87cad2c"},"schema_version":"1.0","source":{"id":"2203.03768","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.03768","created_at":"2026-06-02T01:03:27Z"},{"alias_kind":"arxiv_version","alias_value":"2203.03768v1","created_at":"2026-06-02T01:03:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.03768","created_at":"2026-06-02T01:03:27Z"},{"alias_kind":"pith_short_12","alias_value":"PM4PYAWQ22ZO","created_at":"2026-06-02T01:03:27Z"},{"alias_kind":"pith_short_16","alias_value":"PM4PYAWQ22ZOTJWI","created_at":"2026-06-02T01:03:27Z"},{"alias_kind":"pith_short_8","alias_value":"PM4PYAWQ","created_at":"2026-06-02T01:03:27Z"}],"graph_snapshots":[{"event_id":"sha256:2127dc8c9665033f727b24f8e39f8b53c3fa74ea813a65992142bcb9f1371985","target":"graph","created_at":"2026-06-02T01:03:27Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2203.03768/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Convolutional neural networks (CNNs) have dominated the field of computer vision for nearly a decade due to their strong ability to learn local features. However, due to their limited receptive field, CNNs fail to model the global context. On the other hand, transformer, an attention-based architecture can model the global context easily. Despite this, there are limited studies that investigate the effectiveness of transformers in crowd counting. In addition, the majority of the existing crowd counting methods are based on the regression of density maps which requires point-level annotation of","authors_text":"Siddharth Singh Savner, Vivek kanhangad","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-07T23:10:40Z","title":"CrowdFormer: Weakly-supervised Crowd counting with Improved Generalizability"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.03768","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:63ce3d885608c962a606f145222b37baf4f621ed3d741afe8da885e3e9e15f81","target":"record","created_at":"2026-06-02T01:03:27Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"6e405f5addb0efbbafc35400c1103c7661b02cc455849616f72c42e9a86823aa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-07T23:10:40Z","title_canon_sha256":"90f79cba72d0045f99f58fe515488e3dcf4353cee8744498022fcb1ca87cad2c"},"schema_version":"1.0","source":{"id":"2203.03768","kind":"arxiv","version":1}},"canonical_sha256":"7b38fc02d0d6b2e9a6c87fd1e8597aa2d47d2634312873784253c20da5feb854","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7b38fc02d0d6b2e9a6c87fd1e8597aa2d47d2634312873784253c20da5feb854","first_computed_at":"2026-06-02T01:03:27.659905Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T01:03:27.659905Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wDnvi6ML2nm3+jtM+P3Jcz9Dnmz1afyFZB6MFkBlkufb780LIWj7uDoOn3HcIKDowCCMX5M7YYabY1NXcOH5BQ==","signature_status":"signed_v1","signed_at":"2026-06-02T01:03:27.660243Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.03768","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:63ce3d885608c962a606f145222b37baf4f621ed3d741afe8da885e3e9e15f81","sha256:2127dc8c9665033f727b24f8e39f8b53c3fa74ea813a65992142bcb9f1371985"],"state_sha256":"8bb5f5f5b4d8e212a6babda86c072e5c1554ade88eaf161c0313b1c4b11b5ac7"}