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Single-image SVBRDF capture with a rendering-aware deep network
2018
ACM Transactions on Graphics
Texture, highlights, and shading are some of many visual cues that allow humans to perceive material appearance in single pictures. Yet, recovering spatially-varying bi-directional reflectance distribution functions (SVBRDFs) from a single image based on such cues has challenged researchers in computer graphics for decades. We tackle lightweight appearance capture by training a deep neural network to automatically extract and make sense of these visual cues. Once trained, our network is capable
doi:10.1145/3197517.3201378
fatcat:zgnw562v4faxdo6rv74a63rf7y