{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:S3QSSMBNXYKNCFUTLXDKFLIYIF","short_pith_number":"pith:S3QSSMBN","schema_version":"1.0","canonical_sha256":"96e129302dbe14d116935dc6a2ad184165dc1de34d644b744c4b49b7a7ec0882","source":{"kind":"arxiv","id":"2106.01088","version":4},"attestation_state":"computed","paper":{"title":"TSI: Temporal Saliency Integration for Video Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dongliang Wang, Haisheng Su, Jinyuan Feng, Kunchang Li, Weihao Gan, Wei Wu, Yu Qiao","submitted_at":"2021-06-02T11:43:49Z","abstract_excerpt":"Efficient spatiotemporal modeling is an important yet challenging problem for video action recognition. Existing state-of-the-art methods exploit neighboring feature differences to obtain motion clues for short-term temporal modeling with a simple convolution. However, only one local convolution is incapable of handling various kinds of actions because of the limited receptive field. Besides, action-irrelated noises brought by camera movement will also harm the quality of extracted motion features. In this paper, we propose a Temporal Saliency Integration (TSI) block, which mainly contains a S"},"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":"2106.01088","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-06-02T11:43:49Z","cross_cats_sorted":[],"title_canon_sha256":"d022906aab0728fb92751d37ff0740b013751617934608f9527ac4315f4115d7","abstract_canon_sha256":"295ff6391b1b16ab8db5d7a0882e45887a9000c4d23cbb6ce142b3d80d231512"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:41:39.405457Z","signature_b64":"D1AtOC5/duoF1xaKqdT1vwAwxoe/rkAiz4V8rRnI19OEkqSVEUPFBeju2gXHFpHVhS3Tdwgnu3F1WIn+gCzrDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"96e129302dbe14d116935dc6a2ad184165dc1de34d644b744c4b49b7a7ec0882","last_reissued_at":"2026-07-05T03:41:39.405069Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:41:39.405069Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"TSI: Temporal Saliency Integration for Video Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dongliang Wang, Haisheng Su, Jinyuan Feng, Kunchang Li, Weihao Gan, Wei Wu, Yu Qiao","submitted_at":"2021-06-02T11:43:49Z","abstract_excerpt":"Efficient spatiotemporal modeling is an important yet challenging problem for video action recognition. Existing state-of-the-art methods exploit neighboring feature differences to obtain motion clues for short-term temporal modeling with a simple convolution. However, only one local convolution is incapable of handling various kinds of actions because of the limited receptive field. Besides, action-irrelated noises brought by camera movement will also harm the quality of extracted motion features. In this paper, we propose a Temporal Saliency Integration (TSI) block, which mainly contains a S"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.01088","kind":"arxiv","version":4},"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/2106.01088/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":"2106.01088","created_at":"2026-07-05T03:41:39.405123+00:00"},{"alias_kind":"arxiv_version","alias_value":"2106.01088v4","created_at":"2026-07-05T03:41:39.405123+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.01088","created_at":"2026-07-05T03:41:39.405123+00:00"},{"alias_kind":"pith_short_12","alias_value":"S3QSSMBNXYKN","created_at":"2026-07-05T03:41:39.405123+00:00"},{"alias_kind":"pith_short_16","alias_value":"S3QSSMBNXYKNCFUT","created_at":"2026-07-05T03:41:39.405123+00:00"},{"alias_kind":"pith_short_8","alias_value":"S3QSSMBN","created_at":"2026-07-05T03:41:39.405123+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/S3QSSMBNXYKNCFUTLXDKFLIYIF","json":"https://pith.science/pith/S3QSSMBNXYKNCFUTLXDKFLIYIF.json","graph_json":"https://pith.science/api/pith-number/S3QSSMBNXYKNCFUTLXDKFLIYIF/graph.json","events_json":"https://pith.science/api/pith-number/S3QSSMBNXYKNCFUTLXDKFLIYIF/events.json","paper":"https://pith.science/paper/S3QSSMBN"},"agent_actions":{"view_html":"https://pith.science/pith/S3QSSMBNXYKNCFUTLXDKFLIYIF","download_json":"https://pith.science/pith/S3QSSMBNXYKNCFUTLXDKFLIYIF.json","view_paper":"https://pith.science/paper/S3QSSMBN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2106.01088&json=true","fetch_graph":"https://pith.science/api/pith-number/S3QSSMBNXYKNCFUTLXDKFLIYIF/graph.json","fetch_events":"https://pith.science/api/pith-number/S3QSSMBNXYKNCFUTLXDKFLIYIF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/S3QSSMBNXYKNCFUTLXDKFLIYIF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/S3QSSMBNXYKNCFUTLXDKFLIYIF/action/storage_attestation","attest_author":"https://pith.science/pith/S3QSSMBNXYKNCFUTLXDKFLIYIF/action/author_attestation","sign_citation":"https://pith.science/pith/S3QSSMBNXYKNCFUTLXDKFLIYIF/action/citation_signature","submit_replication":"https://pith.science/pith/S3QSSMBNXYKNCFUTLXDKFLIYIF/action/replication_record"}},"created_at":"2026-07-05T03:41:39.405123+00:00","updated_at":"2026-07-05T03:41:39.405123+00:00"}