Art-directing Appearance using an Environment Map Latent Space

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dc.contributor.authorPetikam, Lohiten_US
dc.contributor.authorChalmers, Andrewen_US
dc.contributor.authorAnjyo, Kenen_US
dc.contributor.authorRhee, Taehyunen_US
dc.contributor.editorLee, Sung-Hee and Zollmann, Stefanie and Okabe, Makoto and Wünsche, Burkharden_US
dc.date.accessioned2021-10-14T10:05:40Z
dc.date.available2021-10-14T10:05:40Z
dc.date.issued2021
dc.description.abstractIn look development, environment maps (EMs) are used to verify 3D appearance in varied lighting (e.g., overcast, sunny, and indoor). Artists can only assign one fixed material, making it laborious to edit appearance uniquely for all EMs. Artists can artdirect material and lighting in film post-production. However, this is impossible in dynamic real-time games and live augmented reality (AR), where environment lighting is unpredictable. We present a new workflow to customize appearance variation across a wide range of EM lighting, for live applications. Appearance edits can be predefined, and then automatically adapted to environment lighting changes. We achieve this by learning a novel 2D latent space of varied EM lighting. The latent space lets artists browse EMs in a semantically meaningful 2D view. For different EMs, artists can paint different material and lighting parameter values directly on the latent space. We robustly encode new EMs into the same space, for automatic look-up of the desired appearance. This solves a new problem of preserving art-direction in live applications, without any artist intervention.en_US
dc.description.sectionheadersNeural Rendering and 3D Models
dc.description.seriesinformationPacific Graphics Short Papers, Posters, and Work-in-Progress Papers
dc.identifier.doi10.2312/pg.20211386
dc.identifier.isbn978-3-03868-162-5
dc.identifier.pages43-48
dc.identifier.urihttps://doi.org/10.2312/pg.20211386
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/pg20211386
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectDimensionality reduction and manifold learning
dc.subjectRendering
dc.titleArt-directing Appearance using an Environment Map Latent Spaceen_US
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