EdgeFace is a novel face recognition model optimized for use on devices with limited processing power and storage. This lightweight face recognition network is inspired by the hybrid architecture of EdgeNeXt, which combines the strengths of convolutional neural networks (CNNs) and transformers to perform accurate face recognition while conserving computational resources.
However, with the introduction of newer models like vision transformers (ViTs), the technology shows a promising approach to enhancing face recognition by effectively capturing long-range interactions. Researchers have extended the existing EdgeNeXt architecture tailored for face recognition on next-generation edge devices.
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