Large-scale three-dimensional face synthesis system for sample similarity suppression
A three-dimensional face and similarity technology, applied in the field of three-dimensional face reconstruction, can solve the problem that the optimization model does not consider the special requirements of face data privacy, and achieve the effect of meeting the special requirements of privacy and improving computing power.
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Embodiment 1
[0042] figure 1 A large-scale three-dimensional face synthesis system for sample similarity suppression according to an exemplary embodiment of the present invention is shown, including:
[0043] A three-dimensional scanning device, configured to acquire a three-dimensional face model and its point cloud data, and output them to the first processing module;
[0044] The first processing module is configured to preprocess the acquired 3D face model to obtain a first 3D face model set; and output the first 3D face model set to the second processing module and the The third processing module;
[0045] The second processing module is used to configure a large-scale three-dimensional face synthesis network model (the large-scale three-dimensional face synthesis network model is a trained generative confrontation network model fused with a self-attention network), the scale three-dimensional face synthesis network The model can synthesize a three-dimensional face model according t...
Embodiment 2
[0054] In a further embodiment of the present invention, a large-scale three-dimensional face synthesis method with sample similarity suppression is also provided, including:
[0055] Step 1, using a 3D scanning device to obtain a 3D face model, and preprocessing the obtained 3D face model through the first processing module, to obtain the following: image 3 The first three-dimensional face model set shown, and output to the second processing module and the third processing module
[0056] Step 2, the large-scale 3D face synthesis network model configured in the second processing module, input the first 3D face model set to the large-scale 3D face synthesis network model to synthesize the 3D face model, and obtain the following: Figure 5 The synthetic three-dimensional human face model shown is output to the third processing module;
[0057] Simultaneously, the third processing module down-samples the first three-dimensional face model set to obtain the following Figure 4...
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