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Hyo-Eun Kim

2 accepted papers

2019

SRM: A Style-Based Recalibration Module for Convolutional Neural Networks

ICCV 2019poster

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, we aim to fully leverage the potential of styles to improve the performance of CNNs in general vision tasks. We propose…

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2018

Batch-Instance Normalization for Adaptively Style-Invariant Neural Networks

NeurIPS 2018poster

Real-world image recognition is often challenged by the variability of visual styles including object textures, lighting conditions, filter effects, etc. Although these variations have been deemed to be implicitly handled by more training data and deeper networks, recent advances in image style tran…