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To bridge this gap, we propose to shift the paradigm into training a powerful delighting network as a prior to constrain the optimization. We leverage the OLAT dataset and the rendered Light Stage scans for training, and propose Dataset Latent Modulation (DLM) to seamlessly integrate these heterogeneous data sources. Specifically, by conditioning the core network on learnable source-aware tokens, we decouple dataset-specific styles from physical delighting principles, enabling the emergence of a delighting prior that outperforms existing proprietary models. This powerful delighting prior enables a simple and automatic appearance capture pipeline that achieves high-quality reflectance estimation from casual video inputs, outperforming prior arts by a large margin. Furthermore, we leverage our appearance capture method to transform the multi-view NeRSemble dataset into NeRSemble-Scan, a large-scale collection of 4K-resolution relightable scans. By open-sourcing our model and the NeRSemble-Scan dataset, we democratize high-end facial capture and provide a new foundation for the research community to build photorealistic digital humans.<\/jats:p>","DOI":"10.1145\/3811303","type":"journal-article","created":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T07:05:51Z","timestamp":1783062351000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Learning a Delighting Prior for Facial Appearance Capture in the Wild"],"prefix":"10.1145","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2844-5074","authenticated-orcid":false,"given":"Yuxuan","family":"Han","sequence":"first","affiliation":[{"name":"School of Software and BNRist, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9602-6078","authenticated-orcid":false,"given":"Xin","family":"Ming","sequence":"additional","affiliation":[{"name":"School of Software and BNRist, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-5136-6005","authenticated-orcid":false,"given":"Tianxiao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Software and BNRist, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5737-4917","authenticated-orcid":false,"given":"Zhuofan","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Software and BNRist, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4837-7152","authenticated-orcid":false,"given":"Qixuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"ShanghaiTech University, Shanghai, China"},{"name":"Deemos Technology Co., Ltd., Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8807-7787","authenticated-orcid":false,"given":"Lan","family":"Xu","sequence":"additional","affiliation":[{"name":"ShanghaiTech University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0953-1057","authenticated-orcid":false,"given":"Feng","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Software and BNRist, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,7,3]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2503385.2503387"},{"key":"e_1_2_2_2_1","doi-asserted-by":"crossref","unstructured":"Oleg Alexander Mike Rogers William Lambeth Matt Chiang and Paul Debevec. 2009. 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