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Found 4 papers, 1 papers with code
MDAN: Multi-level Dependent Attention Network for Visual Emotion Analysis
Existing deep approaches try to bridge the gap by directly learning discrimination among emotions globally in one shot without considering the hierarchical relationship among emotions at different affective levels and the affective level of emotions to be classified.
Towards thinner convolutional neural networks through Gradually Global Pruning
Deep network pruning is an effective method to reduce the storage and computation cost of deep neural networks when applying them to resource-limited devices.
Attribute-controlled face photo synthesis from simple line drawing
In this paper, we propose a deep generative model to synthesize face photo from simple line drawing controlled by face attributes such as hair color and complexion.
Every Filter Extracts A Specific Texture In Convolutional Neural Networks
We also demonstrate that style of images could be a combination of these texture primitives.
