{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:S75ROY4FEXLLDX2AB6JF7ONO6C","short_pith_number":"pith:S75ROY4F","schema_version":"1.0","canonical_sha256":"97fb17638525d6b1df400f925fb9aef093c2fea8b3413b00bf3d824bf7250573","source":{"kind":"arxiv","id":"2404.06033","version":2},"attestation_state":"computed","paper":{"title":"Little Strokes Fell Great Oaks: Boosting the Hierarchical Features for Multi-exposure Image Fusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cong Bai, Jinyuan Liu, Pan Mu, Zhiying Du","submitted_at":"2024-04-09T05:44:00Z","abstract_excerpt":"In recent years, deep learning networks have made remarkable strides in the domain of multi-exposure image fusion. Nonetheless, prevailing approaches often involve directly feeding over-exposed and under-exposed images into the network, which leads to the under-utilization of inherent information present in the source images. Additionally, unsupervised techniques predominantly employ rudimentary weighted summation for color channel processing, culminating in an overall desaturated final image tone. To partially mitigate these issues, this study proposes a gamma correction module specifically d"},"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":"2404.06033","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-09T05:44:00Z","cross_cats_sorted":[],"title_canon_sha256":"91279f5a91d2abfa503b8a006b19bca248006473dd9d8099f4907c332f8e4383","abstract_canon_sha256":"0cbbfb33f885dbb41f3aa091015a9f2094a5f282bb8442ab9820fc050ebcde36"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:06:29.257043Z","signature_b64":"aKd1uM1vAG73acdbJBWCK1ucVtECt/9SBc7ywPBvc/UtE1LP9f8hjcT+DnB1PHY3mEPiid8ZQR2C/DYTUIloAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97fb17638525d6b1df400f925fb9aef093c2fea8b3413b00bf3d824bf7250573","last_reissued_at":"2026-07-05T08:06:29.256577Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:06:29.256577Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Little Strokes Fell Great Oaks: Boosting the Hierarchical Features for Multi-exposure Image Fusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cong Bai, Jinyuan Liu, Pan Mu, Zhiying Du","submitted_at":"2024-04-09T05:44:00Z","abstract_excerpt":"In recent years, deep learning networks have made remarkable strides in the domain of multi-exposure image fusion. Nonetheless, prevailing approaches often involve directly feeding over-exposed and under-exposed images into the network, which leads to the under-utilization of inherent information present in the source images. Additionally, unsupervised techniques predominantly employ rudimentary weighted summation for color channel processing, culminating in an overall desaturated final image tone. To partially mitigate these issues, this study proposes a gamma correction module specifically d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.06033","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/2404.06033/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":"2404.06033","created_at":"2026-07-05T08:06:29.256636+00:00"},{"alias_kind":"arxiv_version","alias_value":"2404.06033v2","created_at":"2026-07-05T08:06:29.256636+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.06033","created_at":"2026-07-05T08:06:29.256636+00:00"},{"alias_kind":"pith_short_12","alias_value":"S75ROY4FEXLL","created_at":"2026-07-05T08:06:29.256636+00:00"},{"alias_kind":"pith_short_16","alias_value":"S75ROY4FEXLLDX2A","created_at":"2026-07-05T08:06:29.256636+00:00"},{"alias_kind":"pith_short_8","alias_value":"S75ROY4F","created_at":"2026-07-05T08:06:29.256636+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/S75ROY4FEXLLDX2AB6JF7ONO6C","json":"https://pith.science/pith/S75ROY4FEXLLDX2AB6JF7ONO6C.json","graph_json":"https://pith.science/api/pith-number/S75ROY4FEXLLDX2AB6JF7ONO6C/graph.json","events_json":"https://pith.science/api/pith-number/S75ROY4FEXLLDX2AB6JF7ONO6C/events.json","paper":"https://pith.science/paper/S75ROY4F"},"agent_actions":{"view_html":"https://pith.science/pith/S75ROY4FEXLLDX2AB6JF7ONO6C","download_json":"https://pith.science/pith/S75ROY4FEXLLDX2AB6JF7ONO6C.json","view_paper":"https://pith.science/paper/S75ROY4F","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2404.06033&json=true","fetch_graph":"https://pith.science/api/pith-number/S75ROY4FEXLLDX2AB6JF7ONO6C/graph.json","fetch_events":"https://pith.science/api/pith-number/S75ROY4FEXLLDX2AB6JF7ONO6C/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/S75ROY4FEXLLDX2AB6JF7ONO6C/action/timestamp_anchor","attest_storage":"https://pith.science/pith/S75ROY4FEXLLDX2AB6JF7ONO6C/action/storage_attestation","attest_author":"https://pith.science/pith/S75ROY4FEXLLDX2AB6JF7ONO6C/action/author_attestation","sign_citation":"https://pith.science/pith/S75ROY4FEXLLDX2AB6JF7ONO6C/action/citation_signature","submit_replication":"https://pith.science/pith/S75ROY4FEXLLDX2AB6JF7ONO6C/action/replication_record"}},"created_at":"2026-07-05T08:06:29.256636+00:00","updated_at":"2026-07-05T08:06:29.256636+00:00"}