{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:3ZFUR2FM7K5NO76GTVGGL2QGY5","short_pith_number":"pith:3ZFUR2FM","schema_version":"1.0","canonical_sha256":"de4b48e8acfabad77fc69d4c65ea06c745ac000771d0cc98899f8203612075ff","source":{"kind":"arxiv","id":"2507.04692","version":2},"attestation_state":"computed","paper":{"title":"Structure-Guided Diffusion Models for High-Fidelity Portrait Shadow Removal","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Qing Zhang, Rongjia Zheng, Wanchang Yu, Wei-Shi Zheng","submitted_at":"2025-07-07T06:19:07Z","abstract_excerpt":"We present a diffusion-based portrait shadow removal approach that can robustly produce high-fidelity results. Unlike previous methods, we cast shadow removal as diffusion-based inpainting. To this end, we first train a shadow-independent structure extraction network on a real-world portrait dataset with various synthetic lighting conditions, which allows to generate a shadow-independent structure map including facial details while excluding the unwanted shadow boundaries. The structure map is then used as condition to train a structure-guided inpainting diffusion model for removing shadows in"},"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":"2507.04692","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-07T06:19:07Z","cross_cats_sorted":[],"title_canon_sha256":"617776b28b344cda262fd4626910684826edce48f5146d5b3496dc3b1a22aa37","abstract_canon_sha256":"5918afaf83a773c966643126a18a0b12f99c7425a710e9a3f2679b32bc879997"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:36:34.458468Z","signature_b64":"/PvXtpTZ16C1LnGogDdPbgTzsaKXKQgf7g30wzsJP0scgiSSPDx3MQmvBvpQx5YOL4MyX9L77bMfyDJ+e1vvDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"de4b48e8acfabad77fc69d4c65ea06c745ac000771d0cc98899f8203612075ff","last_reissued_at":"2026-07-05T11:36:34.457941Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:36:34.457941Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Structure-Guided Diffusion Models for High-Fidelity Portrait Shadow Removal","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Qing Zhang, Rongjia Zheng, Wanchang Yu, Wei-Shi Zheng","submitted_at":"2025-07-07T06:19:07Z","abstract_excerpt":"We present a diffusion-based portrait shadow removal approach that can robustly produce high-fidelity results. Unlike previous methods, we cast shadow removal as diffusion-based inpainting. To this end, we first train a shadow-independent structure extraction network on a real-world portrait dataset with various synthetic lighting conditions, which allows to generate a shadow-independent structure map including facial details while excluding the unwanted shadow boundaries. The structure map is then used as condition to train a structure-guided inpainting diffusion model for removing shadows in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.04692","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/2507.04692/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":"2507.04692","created_at":"2026-07-05T11:36:34.458007+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.04692v2","created_at":"2026-07-05T11:36:34.458007+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.04692","created_at":"2026-07-05T11:36:34.458007+00:00"},{"alias_kind":"pith_short_12","alias_value":"3ZFUR2FM7K5N","created_at":"2026-07-05T11:36:34.458007+00:00"},{"alias_kind":"pith_short_16","alias_value":"3ZFUR2FM7K5NO76G","created_at":"2026-07-05T11:36:34.458007+00:00"},{"alias_kind":"pith_short_8","alias_value":"3ZFUR2FM","created_at":"2026-07-05T11:36:34.458007+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/3ZFUR2FM7K5NO76GTVGGL2QGY5","json":"https://pith.science/pith/3ZFUR2FM7K5NO76GTVGGL2QGY5.json","graph_json":"https://pith.science/api/pith-number/3ZFUR2FM7K5NO76GTVGGL2QGY5/graph.json","events_json":"https://pith.science/api/pith-number/3ZFUR2FM7K5NO76GTVGGL2QGY5/events.json","paper":"https://pith.science/paper/3ZFUR2FM"},"agent_actions":{"view_html":"https://pith.science/pith/3ZFUR2FM7K5NO76GTVGGL2QGY5","download_json":"https://pith.science/pith/3ZFUR2FM7K5NO76GTVGGL2QGY5.json","view_paper":"https://pith.science/paper/3ZFUR2FM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.04692&json=true","fetch_graph":"https://pith.science/api/pith-number/3ZFUR2FM7K5NO76GTVGGL2QGY5/graph.json","fetch_events":"https://pith.science/api/pith-number/3ZFUR2FM7K5NO76GTVGGL2QGY5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3ZFUR2FM7K5NO76GTVGGL2QGY5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3ZFUR2FM7K5NO76GTVGGL2QGY5/action/storage_attestation","attest_author":"https://pith.science/pith/3ZFUR2FM7K5NO76GTVGGL2QGY5/action/author_attestation","sign_citation":"https://pith.science/pith/3ZFUR2FM7K5NO76GTVGGL2QGY5/action/citation_signature","submit_replication":"https://pith.science/pith/3ZFUR2FM7K5NO76GTVGGL2QGY5/action/replication_record"}},"created_at":"2026-07-05T11:36:34.458007+00:00","updated_at":"2026-07-05T11:36:34.458007+00:00"}