{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:F7PWZL5VMGLNESJFBB4W6FUUPO","short_pith_number":"pith:F7PWZL5V","schema_version":"1.0","canonical_sha256":"2fdf6cafb56196d2492508796f16947ba83f77fe811eaa38235f9e7ba43253a7","source":{"kind":"arxiv","id":"2607.08227","version":1},"attestation_state":"computed","paper":{"title":"Multimodal 3D LUT Generation via StatLUT with Statistical Features for Photorealistic Style Transfer","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Congchao Zhu, Yifan Wang, Yu Wang, Zhixiang Hao","submitted_at":"2026-07-09T08:23:04Z","abstract_excerpt":"Photorealistic Style Transfer (PST) aims to transfer the color and tonal style of a reference to a content image while strictly preserving its structural integrity. However, existing deep learning-based methods inherently suffer from semantic entanglement caused by pre-trained image encoders, leading to unnatural spatial distortions. Moreover, current pixel-level mapping paradigms often ignore color gamut topology, resulting in color banding, while also lacking the multimodal capability for intuitive text-driven control. To address these bottlenecks, we propose StatLUT, an innovative multimoda"},"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":"2607.08227","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-09T08:23:04Z","cross_cats_sorted":[],"title_canon_sha256":"bf4c1b7303d5a30fcc742218c6bc0ca7d38b730807cebabc6129c7d0e71c587d","abstract_canon_sha256":"372cc72f3a34016a15096d02bc7e5296ea926f8ca65fb8601c09423c70dfd438"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-10T01:19:30.210183Z","signature_b64":"sPZgSyo49NMyGfTmA/ZwNe4YLGUUgSSNIzXmZ6kxbmy+NQIlmY0zi/ngxbi1gv87UZGrEmzwQG7r13UKxmH1Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2fdf6cafb56196d2492508796f16947ba83f77fe811eaa38235f9e7ba43253a7","last_reissued_at":"2026-07-10T01:19:30.209776Z","signature_status":"signed_v1","first_computed_at":"2026-07-10T01:19:30.209776Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multimodal 3D LUT Generation via StatLUT with Statistical Features for Photorealistic Style Transfer","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Congchao Zhu, Yifan Wang, Yu Wang, Zhixiang Hao","submitted_at":"2026-07-09T08:23:04Z","abstract_excerpt":"Photorealistic Style Transfer (PST) aims to transfer the color and tonal style of a reference to a content image while strictly preserving its structural integrity. However, existing deep learning-based methods inherently suffer from semantic entanglement caused by pre-trained image encoders, leading to unnatural spatial distortions. Moreover, current pixel-level mapping paradigms often ignore color gamut topology, resulting in color banding, while also lacking the multimodal capability for intuitive text-driven control. To address these bottlenecks, we propose StatLUT, an innovative multimoda"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.08227","kind":"arxiv","version":1},"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/2607.08227/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":"2607.08227","created_at":"2026-07-10T01:19:30.209834+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.08227v1","created_at":"2026-07-10T01:19:30.209834+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.08227","created_at":"2026-07-10T01:19:30.209834+00:00"},{"alias_kind":"pith_short_12","alias_value":"F7PWZL5VMGLN","created_at":"2026-07-10T01:19:30.209834+00:00"},{"alias_kind":"pith_short_16","alias_value":"F7PWZL5VMGLNESJF","created_at":"2026-07-10T01:19:30.209834+00:00"},{"alias_kind":"pith_short_8","alias_value":"F7PWZL5V","created_at":"2026-07-10T01:19:30.209834+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/F7PWZL5VMGLNESJFBB4W6FUUPO","json":"https://pith.science/pith/F7PWZL5VMGLNESJFBB4W6FUUPO.json","graph_json":"https://pith.science/api/pith-number/F7PWZL5VMGLNESJFBB4W6FUUPO/graph.json","events_json":"https://pith.science/api/pith-number/F7PWZL5VMGLNESJFBB4W6FUUPO/events.json","paper":"https://pith.science/paper/F7PWZL5V"},"agent_actions":{"view_html":"https://pith.science/pith/F7PWZL5VMGLNESJFBB4W6FUUPO","download_json":"https://pith.science/pith/F7PWZL5VMGLNESJFBB4W6FUUPO.json","view_paper":"https://pith.science/paper/F7PWZL5V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.08227&json=true","fetch_graph":"https://pith.science/api/pith-number/F7PWZL5VMGLNESJFBB4W6FUUPO/graph.json","fetch_events":"https://pith.science/api/pith-number/F7PWZL5VMGLNESJFBB4W6FUUPO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/F7PWZL5VMGLNESJFBB4W6FUUPO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/F7PWZL5VMGLNESJFBB4W6FUUPO/action/storage_attestation","attest_author":"https://pith.science/pith/F7PWZL5VMGLNESJFBB4W6FUUPO/action/author_attestation","sign_citation":"https://pith.science/pith/F7PWZL5VMGLNESJFBB4W6FUUPO/action/citation_signature","submit_replication":"https://pith.science/pith/F7PWZL5VMGLNESJFBB4W6FUUPO/action/replication_record"}},"created_at":"2026-07-10T01:19:30.209834+00:00","updated_at":"2026-07-10T01:19:30.209834+00:00"}