42 citations · 42 across the 1 of their papers we have counts for
4 papers
SRM : A Style-based Recalibration Module for Convolutional Neural Networks
HyunJae Lee, Hyo-Eun Kim, Hyeonseob Nam
Following the advance of style transfer with Convolutional Neural Networks (CNNs), the role of styles in CNNs has drawn growing attention from a broader perspective. In this paper,…
Keep and Learn: Continual Learning by Constraining the Latent Space for Knowledge Preservation in Neural Networks
Hyo-Eun Kim, Seungwook Kim, Jaehwan Lee
Data is one of the most important factors in machine learning. However, even if we have high-quality data, there is a situation in which access to the data is restricted. For examp…
Batch-Instance Normalization for Adaptively Style-Invariant Neural Networks
Hyeonseob Nam, Hyo-Eun Kim
Real-world image recognition is often challenged by the variability of visual styles including object textures, lighting conditions, filter effects, etc. Although these variations…
Deconvolutional Feature Stacking for Weakly-Supervised Semantic Segmentation
Hyo-Eun Kim, Sangheum Hwang
A weakly-supervised semantic segmentation framework with a tied deconvolutional neural network is presented. Each deconvolution layer in the framework consists of unpooling and dec…