{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:NH7LL66WA2NQSJSYFCPM5SI3AH","short_pith_number":"pith:NH7LL66W","schema_version":"1.0","canonical_sha256":"69feb5fbd6069b092658289ecec91b01fb797a78d84c8e1928dbc70b9e1d635d","source":{"kind":"arxiv","id":"1612.04884","version":2},"attestation_state":"computed","paper":{"title":"Scale Coding Bag of Deep Features for Human Attribute and Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrew D. Bagdanov, Fahad Shahbaz Khan, Joost Van De Weijer, Jorma Laaksonen, Michael Felsberg, Rao Muhammad Anwer","submitted_at":"2016-12-14T23:44:23Z","abstract_excerpt":"Most approaches to human attribute and action recognition in still images are based on image representation in which multi-scale local features are pooled across scale into a single, scale-invariant encoding. Both in bag-of-words and the recently popular representations based on convolutional neural networks, local features are computed at multiple scales. However, these multi-scale convolutional features are pooled into a single scale-invariant representation. We argue that entirely scale-invariant image representations are sub-optimal and investigate approaches to scale coding within a Bag o"},"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":"1612.04884","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-14T23:44:23Z","cross_cats_sorted":[],"title_canon_sha256":"2e225c4510c76e623fbba398587905fda89b8b273d822455559b044dd4bad200","abstract_canon_sha256":"ef4dfb54dd39d19f0011dfd0be12441ca670684bcf7036270b014e1bb54ec373"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:20:17.537298Z","signature_b64":"yk1h2FIVqSRNaH1rQxWNV+zE23rWo+mOJYocxuwpvOpnQxF6f7KfHOgZg7RSyUngA2RJRkMehbM3YNldT6ksAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"69feb5fbd6069b092658289ecec91b01fb797a78d84c8e1928dbc70b9e1d635d","last_reissued_at":"2026-05-18T00:20:17.536754Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:20:17.536754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Scale Coding Bag of Deep Features for Human Attribute and Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrew D. Bagdanov, Fahad Shahbaz Khan, Joost Van De Weijer, Jorma Laaksonen, Michael Felsberg, Rao Muhammad Anwer","submitted_at":"2016-12-14T23:44:23Z","abstract_excerpt":"Most approaches to human attribute and action recognition in still images are based on image representation in which multi-scale local features are pooled across scale into a single, scale-invariant encoding. Both in bag-of-words and the recently popular representations based on convolutional neural networks, local features are computed at multiple scales. However, these multi-scale convolutional features are pooled into a single scale-invariant representation. We argue that entirely scale-invariant image representations are sub-optimal and investigate approaches to scale coding within a Bag o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.04884","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":""},"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":"1612.04884","created_at":"2026-05-18T00:20:17.536829+00:00"},{"alias_kind":"arxiv_version","alias_value":"1612.04884v2","created_at":"2026-05-18T00:20:17.536829+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.04884","created_at":"2026-05-18T00:20:17.536829+00:00"},{"alias_kind":"pith_short_12","alias_value":"NH7LL66WA2NQ","created_at":"2026-05-18T12:30:32.724797+00:00"},{"alias_kind":"pith_short_16","alias_value":"NH7LL66WA2NQSJSY","created_at":"2026-05-18T12:30:32.724797+00:00"},{"alias_kind":"pith_short_8","alias_value":"NH7LL66W","created_at":"2026-05-18T12:30:32.724797+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/NH7LL66WA2NQSJSYFCPM5SI3AH","json":"https://pith.science/pith/NH7LL66WA2NQSJSYFCPM5SI3AH.json","graph_json":"https://pith.science/api/pith-number/NH7LL66WA2NQSJSYFCPM5SI3AH/graph.json","events_json":"https://pith.science/api/pith-number/NH7LL66WA2NQSJSYFCPM5SI3AH/events.json","paper":"https://pith.science/paper/NH7LL66W"},"agent_actions":{"view_html":"https://pith.science/pith/NH7LL66WA2NQSJSYFCPM5SI3AH","download_json":"https://pith.science/pith/NH7LL66WA2NQSJSYFCPM5SI3AH.json","view_paper":"https://pith.science/paper/NH7LL66W","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1612.04884&json=true","fetch_graph":"https://pith.science/api/pith-number/NH7LL66WA2NQSJSYFCPM5SI3AH/graph.json","fetch_events":"https://pith.science/api/pith-number/NH7LL66WA2NQSJSYFCPM5SI3AH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NH7LL66WA2NQSJSYFCPM5SI3AH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NH7LL66WA2NQSJSYFCPM5SI3AH/action/storage_attestation","attest_author":"https://pith.science/pith/NH7LL66WA2NQSJSYFCPM5SI3AH/action/author_attestation","sign_citation":"https://pith.science/pith/NH7LL66WA2NQSJSYFCPM5SI3AH/action/citation_signature","submit_replication":"https://pith.science/pith/NH7LL66WA2NQSJSYFCPM5SI3AH/action/replication_record"}},"created_at":"2026-05-18T00:20:17.536829+00:00","updated_at":"2026-05-18T00:20:17.536829+00:00"}