1 code implementation • 20 Feb 2024 • Jaeseok Jeong, Junho Kim, Yunjey Choi, Gayoung Lee, Youngjung Uh
Despite their remarkable capability, existing models still face challenges in achieving controlled generation with a consistent style, requiring costly fine-tuning or often inadequately transferring the visual elements due to content leakage.
no code implementations • 5 Jun 2023 • Sunwoo Kim, Wooseok Jang, Hyunsu Kim, Junho Kim, Yunjey Choi, Seungryong Kim, Gayeong Lee
From the users' standpoint, prompt engineering is a labor-intensive process, and users prefer to provide a target word for editing instead of a full sentence.
no code implementations • 25 May 2023 • Jooyoung Choi, Yunjey Choi, Yunji Kim, Junho Kim, Sungroh Yoon
Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts.
1 code implementation • 26 Feb 2023 • Yoonjeon Kim, Hyunsu Kim, Junho Kim, Yunjey Choi, Eunho Yang
With the advantages of fast inference and human-friendly flexible manipulation, image-agnostic style manipulation via text guidance enables new applications that were not previously available.
1 code implementation • ICCV 2023 • Hyunsu Kim, Gayoung Lee, Yunjey Choi, Jin-Hwa Kim, Jun-Yan Zhu
Image blending aims to combine multiple images seamlessly.
no code implementations • CVPR 2023 • Gyeongman Kim, Hajin Shim, Hyunsu Kim, Yunjey Choi, Junho Kim, Eunho Yang
Inspired by the impressive performance of recent face image editing methods, several studies have been naturally proposed to extend these methods to the face video editing task.
1 code implementation • 27 Jul 2022 • Gayoung Lee, Hyunsu Kim, Junho Kim, Seonghyeon Kim, Jung-Woo Ha, Yunjey Choi
Here we explore the efficacy of dense supervision in unconditional generation and find generator feature maps can be an alternative of cost-expensive semantic label maps.
no code implementations • 4 Jul 2022 • Namwoo Lee, Hyunsu Kim, Gayoung Lee, Sungjoo Yoo, Yunjey Choi
However, training existing approaches require a heavy computational cost proportional to the image resolution, since they compute an MLP operation for every (x, y) coordinate.
1 code implementation • 17 Jun 2022 • Jiyeon Han, Hwanil Choi, Yunjey Choi, Junho Kim, Jung-Woo Ha, Jaesik Choi
In this work, we propose a new evaluation metric, called `rarity score', to measure the individual rarity of each image synthesized by generative models.
1 code implementation • CVPR 2022 • Junho Kim, Yunjey Choi, Youngjung Uh
In generative adversarial networks, improving discriminators is one of the key components for generation performance.
1 code implementation • CVPR 2021 • Hyunsu Kim, Yunjey Choi, Junho Kim, Sungjoo Yoo, Youngjung Uh
Although manipulating the latent vectors controls the synthesized outputs, editing real images with GANs suffers from i) time-consuming optimization for projecting real images to the latent vectors, ii) or inaccurate embedding through an encoder.
no code implementations • 1 Jan 2021 • Hyunsu Kim, Yunjey Choi, Junho Kim, Sungjoo Yoo, Youngjung Uh
State-of-the-art GAN-based methods for editing real images suffer from time-consuming operations in projecting real images to latent vectors.
1 code implementation • ICCV 2021 • Kyungjune Baek, Yunjey Choi, Youngjung Uh, Jaejun Yoo, Hyunjung Shim
To this end, we propose a truly unsupervised image-to-image translation model (TUNIT) that simultaneously learns to separate image domains and translates input images into the estimated domains.
3 code implementations • ICML 2020 • Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, Jaejun Yoo
In this paper, we show that even the latest version of the precision and recall metrics are not reliable yet.
14 code implementations • CVPR 2020 • Yunjey Choi, Youngjung Uh, Jaejun Yoo, Jung-Woo Ha
A good image-to-image translation model should learn a mapping between different visual domains while satisfying the following properties: 1) diversity of generated images and 2) scalability over multiple domains.
Fundus to Angiography Generation Multimodal Unsupervised Image-To-Image Translation +1
34 code implementations • CVPR 2018 • Yunjey Choi, Min-Je Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, Jaegul Choo
To address this limitation, we propose StarGAN, a novel and scalable approach that can perform image-to-image translations for multiple domains using only a single model.
Ranked #1 on Image-to-Image Translation on RaFD (using extra training data)