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20172022
most citedLearning Boost by Exploiting the Auxiliary Task in Multi-task Domain

3 citations · 6 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CV2022

Style-Guided Inference of Transformer for High-resolution Image Synthesis

Jonghwa Yim, Minjae Kim

Transformer is eminently suitable for auto-regressive image synthesis which predicts discrete value from the past values recursively to make up full image. Especially, combined wit…

cs.CV20221 cited

StyLandGAN: A StyleGAN based Landscape Image Synthesis using Depth-map

Gunhee Lee, Jonghwa Yim, Chanran Kim +1

Despite recent success in conditional image synthesis, prevalent input conditions such as semantics and edges are not clear enough to express `Linear (Ridges)' and `Planar (Scale)'…

cs.CV20202 cited

Filter Style Transfer between Photos

Jonghwa Yim, Jisung Yoo, Won-joon Do +2

Over the past few years, image-to-image style transfer has risen to the frontiers of neural image processing. While conventional methods were successful in various tasks such as co…

cs.CV2018

One-Shot Item Search with Multimodal Data

Jonghwa Yim, Junghun James Kim, Daekyu Shin

In the task of near similar image search, features from Deep Neural Network is often used to compare images and measure similarity. In the past, we only focused visual search in im…

cs.CV2017

Investigating the feature collection for semantic segmentation via single skip connection

Jonghwa Yim, Kyung-Ah Sohn

Since the study of deep convolutional neural network became prevalent, one of the important discoveries is that a feature map from a convolutional network can be extracted before g…

cs.CV2017

Enhancing the Performance of Convolutional Neural Networks on Quality Degraded Datasets

Jonghwa Yim, Kyung-Ah Sohn

Despite the appeal of deep neural networks that largely replace the traditional handmade filters, they still suffer from isolated cases that cannot be properly handled only by the…