Search Results for author: Min-Cheol Sagong

Found 6 papers, 0 papers with code

VIGFace: Virtual Identity Generation Model for Face Image Synthesis

no code implementations13 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.

Face Recognition Image Generation

Image Generation with Self Pixel-wise Normalization

no code implementations26 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.

Generative Adversarial Network Image-to-Image Translation

cGANs with Conditional Convolution Layer

no code implementations3 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.

Conditional Image Generation

PEPSI : Fast Image Inpainting With Parallel Decoding Network

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.

Generative Adversarial Network Image Inpainting

PEPSI++: Fast and Lightweight Network for Image Inpainting

no code implementations22 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.

Generative Adversarial Network Image Inpainting +1

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