{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:2ZKRVYQUJLE52FCWTA4S6SLTPB","short_pith_number":"pith:2ZKRVYQU","schema_version":"1.0","canonical_sha256":"d6551ae2144ac9dd145698392f4973786f9854bae0ce09ab2cfeb4813dc975c7","source":{"kind":"arxiv","id":"2106.10472","version":2},"attestation_state":"computed","paper":{"title":"Informative Class Activation Maps","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Dongwoo Kim, Tom Gedeon, Zhenyue Qin","submitted_at":"2021-06-19T11:02:59Z","abstract_excerpt":"We study how to evaluate the quantitative information content of a region within an image for a particular label. To this end, we bridge class activation maps with information theory. We develop an informative class activation map (infoCAM). Given a classification task, infoCAM depict how to accumulate information of partial regions to that of the entire image toward a label. Thus, we can utilise infoCAM to locate the most informative features for a label. When applied to an image classification task, infoCAM performs better than the traditional classification map in the weakly supervised obje"},"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":"2106.10472","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-19T11:02:59Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"76c724b118cf85b8ca607f0978f3c10c0920661250ea02e9de25a515d0fd53fc","abstract_canon_sha256":"0df9790457da2e87bd3208e2c47f76f70efb4ec33a178d51767617ad42e44599"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:05:51.377077Z","signature_b64":"KZWX23KS/BJzMwWHQxCgIYRgQLvJF3qvHJHSWN9YD6f4dXrYgF2D+/3CkIh/cDXHLrQb46sBhgSe3L3FE6uwDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6551ae2144ac9dd145698392f4973786f9854bae0ce09ab2cfeb4813dc975c7","last_reissued_at":"2026-07-05T03:05:51.376497Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:05:51.376497Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Informative Class Activation Maps","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Dongwoo Kim, Tom Gedeon, Zhenyue Qin","submitted_at":"2021-06-19T11:02:59Z","abstract_excerpt":"We study how to evaluate the quantitative information content of a region within an image for a particular label. To this end, we bridge class activation maps with information theory. We develop an informative class activation map (infoCAM). Given a classification task, infoCAM depict how to accumulate information of partial regions to that of the entire image toward a label. Thus, we can utilise infoCAM to locate the most informative features for a label. When applied to an image classification task, infoCAM performs better than the traditional classification map in the weakly supervised obje"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.10472","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/2106.10472/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":"2106.10472","created_at":"2026-07-05T03:05:51.376578+00:00"},{"alias_kind":"arxiv_version","alias_value":"2106.10472v2","created_at":"2026-07-05T03:05:51.376578+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.10472","created_at":"2026-07-05T03:05:51.376578+00:00"},{"alias_kind":"pith_short_12","alias_value":"2ZKRVYQUJLE5","created_at":"2026-07-05T03:05:51.376578+00:00"},{"alias_kind":"pith_short_16","alias_value":"2ZKRVYQUJLE52FCW","created_at":"2026-07-05T03:05:51.376578+00:00"},{"alias_kind":"pith_short_8","alias_value":"2ZKRVYQU","created_at":"2026-07-05T03:05:51.376578+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/2ZKRVYQUJLE52FCWTA4S6SLTPB","json":"https://pith.science/pith/2ZKRVYQUJLE52FCWTA4S6SLTPB.json","graph_json":"https://pith.science/api/pith-number/2ZKRVYQUJLE52FCWTA4S6SLTPB/graph.json","events_json":"https://pith.science/api/pith-number/2ZKRVYQUJLE52FCWTA4S6SLTPB/events.json","paper":"https://pith.science/paper/2ZKRVYQU"},"agent_actions":{"view_html":"https://pith.science/pith/2ZKRVYQUJLE52FCWTA4S6SLTPB","download_json":"https://pith.science/pith/2ZKRVYQUJLE52FCWTA4S6SLTPB.json","view_paper":"https://pith.science/paper/2ZKRVYQU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2106.10472&json=true","fetch_graph":"https://pith.science/api/pith-number/2ZKRVYQUJLE52FCWTA4S6SLTPB/graph.json","fetch_events":"https://pith.science/api/pith-number/2ZKRVYQUJLE52FCWTA4S6SLTPB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2ZKRVYQUJLE52FCWTA4S6SLTPB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2ZKRVYQUJLE52FCWTA4S6SLTPB/action/storage_attestation","attest_author":"https://pith.science/pith/2ZKRVYQUJLE52FCWTA4S6SLTPB/action/author_attestation","sign_citation":"https://pith.science/pith/2ZKRVYQUJLE52FCWTA4S6SLTPB/action/citation_signature","submit_replication":"https://pith.science/pith/2ZKRVYQUJLE52FCWTA4S6SLTPB/action/replication_record"}},"created_at":"2026-07-05T03:05:51.376578+00:00","updated_at":"2026-07-05T03:05:51.376578+00:00"}