58 citations · 93 across the 9 of their papers we have counts for
9 papers
WaveDH: Wavelet Sub-bands Guided ConvNet for Efficient Image Dehazing
Seongmin Hwang, Daeyoung Han, Cheolkon Jung +1
The surge in interest regarding image dehazing has led to notable advancements in deep learning-based single image dehazing approaches, exhibiting impressive performance in recent…
SuperStyleNet: Deep Image Synthesis with Superpixel Based Style Encoder
Jonghyun Kim, Gen Li, Cheolkon Jung +1
Existing methods for image synthesis utilized a style encoder based on stacks of convolutions and pooling layers to generate style codes from input images. However, the encoded vec…
Edge and Identity Preserving Network for Face Super-Resolution
Jonghyun Kim, Gen Li, Inyong Yun +2
Face super-resolution (SR) has become an indispensable function in security solutions such as video surveillance and identification system, but the distortion in facial components…
Adversarial Defense by Suppressing High-frequency Components
Zhendong Zhang, Cheolkon Jung, Xiaolong Liang
Recent works show that deep neural networks trained on image classification dataset bias towards textures. Those models are easily fooled by applying small high-frequency perturbat…
GBDT-MO: Gradient Boosted Decision Trees for Multiple Outputs
Zhendong Zhang, Cheolkon Jung
Gradient boosted decision trees (GBDTs) are widely used in machine learning, and the output of current GBDT implementations is a single variable. When there are multiple outputs, G…
Attention-Aware Linear Depthwise Convolution for Single Image Super-Resolution
Seongmin Hwang, Gwanghuyn Yu, Cheolkon Jung +1
Although deep convolutional neural networks (CNNs) have obtained outstanding performance in image superresolution (SR), their computational cost increases geometrically as CNN mode…
Recurrent Convolution for Compact and Cost-Adjustable Neural Networks: An Empirical Study
Zhendong Zhang, Cheolkon Jung
Recurrent convolution (RC) shares the same convolutional kernels and unrolls them multiple steps, which is originally proposed to model time-space signals. We argue that RC can be…
PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report
Andrey Ignatov, Radu Timofte, Thang Van Vu +45
This paper reviews the first challenge on efficient perceptual image enhancement with the focus on deploying deep learning models on smartphones. The challenge consisted of two tra…
Part-Level Convolutional Neural Networks for Pedestrian Detection Using Saliency and Boundary Box Alignment
Inyong Yun, Cheolkon Jung, Xinran Wang +2
Pedestrians in videos have a wide range of appearances such as body poses, occlusions, and complex backgrounds, and there exists the proposal shift problem in pedestrian detection…