Search Results for author: Eungyeup Kim

Found 5 papers, 2 papers with code

BiaSwap: Removing dataset bias with bias-tailored swapping augmentation

no code implementations ICCV 2021 Eungyeup Kim, Jihyeon Lee, Jaegul Choo

Although previous approaches pre-define the type of dataset bias to prevent the network from learning it, recognizing the bias type in the real dataset is often prohibitive.

Action Recognition Facial Attribute Classification

Deep Edge-Aware Interactive Colorization against Color-Bleeding Effects

1 code implementation ICCV 2021 Eungyeup Kim, Sanghyeon Lee, Jeonghoon Park, Somi Choi, Choonghyun Seo, Jaegul Choo

Deep neural networks for automatic image colorization often suffer from the color-bleeding artifact, a problematic color spreading near the boundaries between adjacent objects.

Colorization Image Colorization

Learning Debiased Representation via Disentangled Feature Augmentation

1 code implementation NeurIPS 2021 Jungsoo Lee, Eungyeup Kim, Juyoung Lee, Jihyeon Lee, Jaegul Choo

To this end, our method learns the disentangled representation of (1) the intrinsic attributes (i. e., those inherently defining a certain class) and (2) bias attributes (i. e., peripheral attributes causing the bias), from a large number of bias-aligned samples, the bias attributes of which have strong correlation with the target variable.

Data Augmentation Image Classification

Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence

no code implementations CVPR 2020 Junsoo Lee, Eungyeup Kim, Yunsung Lee, Dongjun Kim, Jaehyuk Chang, Jaegul Choo

However, it is difficult to prepare for a training data set that has a sufficient amount of semantically meaningful pairs of images as well as the ground truth for a colored image reflecting a given reference (e. g., coloring a sketch of an originally blue car given a reference green car).

Colorization Image Colorization +1

Unpaired Image Translation via Adaptive Convolution-based Normalization

no code implementations29 Nov 2019 Wonwoong Cho, Kangyeol Kim, Eungyeup Kim, Hyunwoo J. Kim, Jaegul Choo

Disentangling content and style information of an image has played an important role in recent success in image translation.

Translation

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