基于快速下采样的轻量化网络设计方法及人脸识别应用

Translated title of the contribution: Lightweight Network Design and Application for Face Recognition Based on Fast Down-Sampling

Jia Hao Wang, Shu Gong Xu*, Heng Jie Lu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

High-precision convolutional neural networks often come with high inference costs, making it difficult to perform real-time inference on resource-constrained embedded devices. We analyze the factors that influence the speed of model inference by different types of convolutions, and for the first time point out that in addition to the computational complexity of the model, the feature map throughput of the model is also a key factor affecting the inference speed. However, the existing lightweight methods based on the depth-wise separation convolution only use computational complexity as the model lightweight metric, not considering the influence of the feature map throughput on the model inference speed. Based on this discovery, we propose a model lightweight acceleration design method combined with standard convolution based on fast down-sampling module, which could reduce the computational complexity and feature map throughput of the model at the same time by rapidly reducing the size of the feature map. The performance and the inference speed on different platforms of the models designed by proposed method are better than the existing lightweight methods based on depth-wise separation convolution. Further, we utilize this method to propose a fast face recognition model FDFaceNet(Fast Down-sampling FaceNet)for face recognition tasks. Compared with the existing lightweight face recognition models, FDFaceNet has higher accuracy and faster inference speed on various platforms.

Translated title of the contributionLightweight Network Design and Application for Face Recognition Based on Fast Down-Sampling
Original languageChinese (Traditional)
Pages (from-to)2226-2237
Number of pages12
JournalTien Tzu Hsueh Pao/Acta Electronica Sinica
Volume51
Issue number8
DOIs
Publication statusPublished - Aug 2023
Externally publishedYes

Keywords

  • embedded devices
  • face detection and recognition system
  • lightweight face recognition
  • lightweight neural network design
  • neural network acceleration

Fingerprint

Dive into the research topics of 'Lightweight Network Design and Application for Face Recognition Based on Fast Down-Sampling'. Together they form a unique fingerprint.

Cite this