网络编译 作者说我们提出的网络充分使用了depthwise分解,并且depth wise separable convolutional layers并没有在现有的深度学习框架上进行优化,所以这促使作者和需要对特定硬件来编译他们的代码,使得在硬件上减少运算的时间,作者在这里使用的是TVM complier。 网络剪枝 为了进一步减少网络的运行时间,作者用了一个sota的剪枝...
It is composed of residual blocks with 1D depth-wise separable convolutions, batch-normalization, and ReLU layers. This architecture uses x-vector based statistics pooling layer to map variable-length utterances to a fixed-length embedding (q-vector). SpeakerNet-M is a simple lightweight model ...
The inclusion of depth wise component and squeeze-and-excitation results in better performance by capturing a more receptive field than the traditional convolutional layer; however, the parameters are almost the same. To improve the performance and training set, we have combined three large scale ...
I thought of to use separate 2*normal convolutions at initial block, while other blocks uses depthwise convolution. By using normal convolution, this layer can able to fetch more features from the input image and aggragating both convolution output at the concatenation layer will help to provide...
(CNN) has better performances than the two-part structure of traditional machine learning methods. Existing CNN architectures use various tricks to improve the performance of steganalysis, such as fixed convolutional kernels, the absolute value layer, data augmentation and the domain knowledge. However,...
adopts the same weight sharing method as ordinary depth-wise convolution: spatial space shared convolution kernel and independent convolution kernel between channels. It also uses Global Average Pooling to process input features and then dynamically predicts dynamic convolution kernel...
We integrate the computation of multi-head attention networks and feed-forward networks with the depth-wise LSTM for the Transformer, which shows how to utilize the depth-wise LSTM like the residual connection. Our experiment with the 6-layer Transformer shows that our approach can bring about ...
Monocular 3D object detection is challenging due to the lack of accurate depth information. Some methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB images. Depth-base
There- fore, we propose to learn depth-aware attention to have pixel-wise 3D geometry constraint on the motion field (see Fig. 1c), to drive the generation with more fine-grained de- tails of facial structure and movements. All the above-illustrated con...
An eight-layer 2D CNN is applied, where the strides of layer 3 and 6 are set to two to divide the feature towers into three scales. Within each scale, two convolutional layers are applied to extract the higher-level image representation. Each convolutional layer is followed by a batch-...