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    • 9. 发明专利
    • Generating three-dimensional facial data
    • GB2585708B
    • 2022-07-06
    • GB201910114
    • 2019-07-15
    • HUAWEI TECH CO LTD
    • BARIC GECERSTEFANOS ZAFEIRIOU
    • G06T17/00G06T13/40G06V40/16
    • A computer-implemented method of generating 3D facial data using a generator neural network 102 comprises: inputting, into the generator network, initialization data 104 which comprises noise; processing the initialisation data through the generator network to generate UV maps 106 in a plurality of modalities, the maps comprise a shape map 108, a texture map 110, and a normal map 112; and outputting facial data 114 which comprises the UV maps. The generator neural network comprises: an initial set of network layers 116 to generate feature maps from the initialisation data; a first branch 122 configured to generate the shape map from one or more feature maps; a second branch 124 to generate the texture map from one or more feature maps; and a third branch 126 to generate the normal map from the one or more feature maps. The generator neural network may be trained using a discriminator network (figure 3; 304) of reciprocal structure. The face data produced by the trained generator network may be used to train a facial recognition neural network (figure 5; 504). The initialisation data may comprise expression data.