Browsing by Author "Martin, Rosalie"

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    De-lighting a High-resolution Picture for Material Acquisition
    (The Eurographics Association, 2019) Martin, Rosalie; Meyer, Arthur; Pesare, Davide; Boubekeur, Tamy and Sen, Pradeep
    We propose a deep-learning based method for the removal of shades, projected shadows and highlights from a single picture of a quasi-planar surface captured in natural lighting conditions with any kind of camera device. To achieve this, we train an encoder-decoder to process physically based materials, rendered under various lighting conditions, to infer its spatially-varying albedo. Our network processes relatively small image tiles (512x512 pixels) and we propose a solution to handle larger image resolutions by solving a Poisson system across these tiles.
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    MaterIA: Single Image High-Resolution Material Capture in the Wild
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Martin, Rosalie; Roullier, Arthur; Rouffet, Romain; Kaiser, Adrien; Boubekeur, Tamy; Chaine, Raphaƫlle; Kim, Min H.
    We propose a hybrid method to reconstruct a physically-based spatially varying BRDF from a single high resolution picture of an outdoor surface captured under natural lighting conditions with any kind of camera device. Relying on both deep learning and explicit processing, our PBR material acquisition handles the removal of shades, projected shadows and specular highlights present when capturing a highly irregular surface and enables to properly retrieve the underlying geometry. To achieve this, we train two cascaded U-Nets on physically-based materials, rendered under various lighting conditions, to infer the spatiallyvarying albedo and normal maps. Our network processes relatively small image tiles (512x512 pixels) and we propose a solution to handle larger image resolutions by solving a Poisson system across these tiles. We complete this pipeline with analytical solutions to reconstruct height, roughness and ambient occlusion.