Low-resolution Face Recognition Based on Super-resolution Reconstruction
The existing face recognition methods are mainly aimed at high-resolution faces,and the recognition effect of existing models is not ideal for low-resolution faces obtained in combat scenes,and super-resolution reconstruction of faces is an effective method to deal with low-resolution faces.The existing research mainly focuses on the visual effect of the reconstructed image,but ignores the recognition rate of the reconstructed results.In view of the existing needs and existing problems,the method of super-resolution reconstruction is studied to improve the recognition rate of low-resolution faces,so as to improve the success rate of precision strike.A super-resolution reconstruction SRR model is proposed,which has certain advantages in visual effect and recognition rate compared with other existing algorithms.
face recognitionsuper-resolution reconstructioncomputer visiongenerative adversarial networkfacial reconstruction
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