no code implementations • 13 Mar 2024 • Minsoo Kim, Min-Cheol Sagong, Gi Pyo Nam, Junghyun Cho, Ig-Jae Kim
Initially, we train the face recognition model using a real face dataset and create a feature space for both real and virtual IDs where virtual prototypes are orthogonal to other prototypes.
no code implementations • 26 Jan 2022 • Yoon-Jae Yeo, Min-Cheol Sagong, Seung Park, Sung-Jea Ko, Yong-Goo Shin
Region-adaptive normalization (RAN) methods have been widely used in the generative adversarial network (GAN)-based image-to-image translation technique.
no code implementations • 28 Jul 2021 • Min-Cheol Sagong, Yoon-Jae Yeo, Seung-Won Jung, Sung-Jea Ko
In addition, we propose an improved information aggregation module with PAKA, called the hierarchical PAKA module (HPM).
no code implementations • 3 Jun 2019 • Min-Cheol Sagong, Yong-Goo Shin, Yoon-Jae Yeo, Seung Park, Sung-Jea Ko
Conditional generative adversarial networks (cGANs) have been widely researched to generate class conditional images using a single generator.
no code implementations • CVPR 2019 • Min-Cheol Sagong, Yong-goo Shin, Seung-wook Kim, Seung Park, Sung-jea Ko
Recently, a generative adversarial network (GAN)-based method employing the coarse-to-fine network with the contextual attention module (CAM) has shown outstanding results in image inpainting.
no code implementations • 22 May 2019 • Yong-Goo Shin, Min-Cheol Sagong, Yoon-Jae Yeo, Seung-Wook Kim, Sung-Jea Ko
To address this problem, we propose a novel network architecture called PEPSI: parallel extended-decoder path for semantic inpainting network, which aims at reducing the hardware costs and improving the inpainting performance.