125 citations · 255 across the 7 of their papers we have counts for
7 papers
Enhancing Stability in Training Conditional Generative Adversarial Networks via Selective Data Matching
Kyeongbo Kong, Kyunghun Kim, Suk-Ju Kang
Conditional generative adversarial networks (cGANs) have demonstrated remarkable success due to their class-wise controllability and superior quality for complex generation tasks.…
Painting Outside as Inside: Edge Guided Image Outpainting via Bidirectional Rearrangement with Progressive Step Learning
Kyunghun Kim, Yeohun Yun, Keon-Woo Kang +3
Image outpainting is a very intriguing problem as the outside of a given image can be continuously filled by considering as the context of the image. This task has two main challen…
An Efficient Accelerator Design Methodology for Deformable Convolutional Networks
Saehyun Ahn, Jung-Woo Chang, Suk-Ju Kang
Deformable convolutional networks have demonstrated outstanding performance in object recognition tasks with an effective feature extraction. Unlike standard convolution, the defor…
End-to-End Differentiable Learning to HDR Image Synthesis for Multi-exposure Images
Jung Hee Kim, Siyeong Lee, Suk-Ju Kang
Recently, high dynamic range (HDR) image reconstruction based on the multiple exposure stack from a given single exposure utilizes a deep learning framework to generate high-qualit…
Towards Design Methodology of Efficient Fast Algorithms for Accelerating Generative Adversarial Networks on FPGAs
Jung-Woo Chang, Saehyun Ahn, Keon-Woo Kang +1
Generative adversarial networks (GANs) have shown excellent performance in image and speech applications. GANs create impressive data primarily through a new type of operator calle…
Deep Chain HDRI: Reconstructing a High Dynamic Range Image from a Single Low Dynamic Range Image
Siyeong Lee, Gwon Hwan An, Suk-Ju Kang
In this paper, we propose a novel deep neural network model that reconstructs a high dynamic range (HDR) image from a single low dynamic range (LDR) image. The proposed model is ba…
An Energy-Efficient FPGA-based Deconvolutional Neural Networks Accelerator for Single Image Super-Resolution
Jung-Woo Chang, Keon-Woo Kang, Suk-Ju Kang
Convolutional neural networks (CNNs) demonstrate excellent performance in various computer vision applications. In recent years, FPGA-based CNN accelerators have been proposed for…