二值网络--TBN: Convolutional Neural Network with Ternary Inputs and

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TBN: Convolutional Neural Network with Ternary Inputs and Binary Weights

ECCV2018

本文的思路就是： 对 weight 进行二值量化+ scaling factor α ， 对于 网络层的输入 进行 ternary value {−1,0,1} without the scaling factor

3 Ternary-Binary Networks

3.1 Convolution with Matrix Multiplication

use matrix multiplication to implement the convolution layer ⟨I,W,∗⟩

ten2mat 将一组滤波器 weight filters W can be reshaped to a matrix

ten2mat reshape the matrix back to output tensor C

3.2 Binary Weights

3.3 Ternary Inputs

the scaling factors of the binary inputs does not affect the performance of XNOR-Networks

这里我们不采用 scaling factor 了

3.4 Ternary-Binary Dot Product

这样卷积就没有乘法运算了，只有 位运算和 加减

量化梯度求导采用：

provides ∼ 32× memory savings and 40× faster convolutional operations

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