![]() ![]() Such high-resolution appearance map(s) and high-resolution 3D geometry can then be used to render standalone images or the frames of a video that include the digital face. The low-resolution appearance map(s) are further processed using a super-resolution generator that is trained to take the low-resolution appearance map(s) and low-resolution 3D geometry of the digital face as inputs and output high-resolution appearance map(s) that align with high-resolution 3D geometry of the digital face. 7025 veena chandran 7024 haritha t 7020 prasanth r k 7019 adarsh s n 7015 gayathri k s 7013 aarif muhammad t 7012 anagha philip antony 7009 remya unnikrishnan 7007 govind m 7006 anand a j. ![]() ![]() The style-based generator is trained to process such inputs and output low-resolution appearance map(s) for the digital face, such as a texture map, a normal map, and/or a specular roughness map. In some examples, a style-based generator receives as inputs initial tensor(s) and style vector(s) corresponding to user-selected semantic attribute styles, such as the desired expression, gender, age, identity, and/or ethnicity of a digital face. Abstract: Techniques are disclosed for generating digital faces. ![]()
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