no code implementations • 2 Apr 2024 • Hongjae Lee, Jun-Sang Yoo, Seung-Won Jung
Single image super-resolution (SISR) aims to reconstruct a high-resolution image from its low-resolution observation.
1 code implementation • 8 Mar 2024 • SeokJun Lee, Seung-Won Jung, Hyunseok Seo
We evaluate our framework across eight fake image datasets and various cutting-edge models to demonstrate the effectiveness of STIG.
no code implementations • 9 Dec 2023 • Kwang-Hyun Uhm, Seung-Won Jung, Moon Hyung Choi, Sung-Hoo Hong, Sung-Jea Ko
In this paper, we propose a unified framework for kidney cancer diagnosis with incomplete multi-phase CT, which simultaneously recovers missing CT images and classifies cancer subtypes using the completed set of images.
no code implementations • 9 Dec 2023 • Kwang-Hyun Uhm, Hyunjun Cho, Zhixin Xu, Seohoon Lim, Seung-Won Jung, Sung-Hoo Hong, Sung-Jea Ko
In 2023, it is estimated that 81, 800 kidney cancer cases will be newly diagnosed, and 14, 890 people will die from this cancer in the United States.
no code implementations • 17 Jul 2023 • Jun-Sang Yoo, Hongjae Lee, Seung-Won Jung
This paper presents a novel framework called HST for semi-supervised video object segmentation (VOS).
no code implementations • 21 Apr 2023 • Yucheng Lu, Zhixin Xu, Moon Hyung Choi, Jimin Kim, Seung-Won Jung
Computed tomography (CT) has been used worldwide as a non-invasive test in assisting diagnosis.
no code implementations • CVPR 2023 • Junyong Choi, SeokYeong Lee, Haesol Park, Seung-Won Jung, Ig-Jae Kim, Junghyun Cho
We propose a scene-level inverse rendering framework that uses multi-view images to decompose the scene into geometry, a SVBRDF, and 3D spatially-varying lighting.
1 code implementation • ICCV 2023 • Jun-Sang Yoo, Hongjae Lee, Seung-Won Jung
In this paper, we propose a video object segmentation (VOS)-aware training framework called VOS-VFI that allows VFI models to interpolate frames with more precise object boundaries.
1 code implementation • 24 Aug 2022 • Jun-Sang Yoo, Dong-Wook Kim, Yucheng Lu, Seung-Won Jung
To advance ZSSR, we obtain reference image patches with rich textures and high-frequency details which are also extracted only from the input image using cross-scale matching.
no code implementations • 16 Aug 2022 • Wooseok Jeong, Seung-Won Jung
In this paper, we investigate the designing of a fully end-to-end optimized camera ISP incorporating image compression.
1 code implementation • 27 Jul 2022 • Hongjae Lee, Changwoo Han, Jun-Sang Yoo, Seung-Won Jung
Nighttime semantic segmentation is especially challenging due to a lack of annotated nighttime images and a large domain gap from daytime images with sufficient annotation.
Ranked #8 on Semantic Segmentation on Dark Zurich
1 code implementation • CVPR 2022 • Seo-won Ji, Jeongmin Lee, Seung-Wook Kim, Jun-Pyo Hong, Seung-Jin Baek, Seung-Won Jung, Sung-Jea Ko
Many convolutional neural networks (CNNs) for single image deblurring employ a U-Net structure to estimate latent sharp images.
4 code implementations • ICCV 2021 • Sung-Jin Cho, Seo-won Ji, Jun-Pyo Hong, Seung-Won Jung, Sung-Jea Ko
Coarse-to-fine strategies have been extensively used for the architecture design of single image deblurring networks.
Ranked #5 on Deblurring on RSBlur
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).
1 code implementation • 28 Jun 2021 • Yucheng Lu, Seung-Won Jung
Low-light imaging on mobile devices is typically challenging due to insufficient incident light coming through the relatively small aperture, resulting in a low signal-to-noise ratio.
2 code implementations • 27 May 2019 • Dong-Wook Kim, Jae Ryun Chung, Seung-Won Jung
In this paper, we propose a grouped residual dense network (GRDN), which is an extended and generalized architecture of the state-of-the-art residual dense network (RDN).