no code implementations • 19 Sep 2023 • Kyungmin Jo, Wonjoon Jin, Jaegul Choo, Hyunjoon Lee, Sunghyun Cho
In this paper, we propose SideGAN, a novel 3D GAN training method to generate photo-realistic images irrespective of the camera pose, especially for faces of side-view angles.
1 code implementation • 9 Mar 2023 • Daeun Kyung, Kyungmin Jo, Jaegul Choo, Joonseok Lee, Edward Choi
X-ray computed tomography (CT) is one of the most common imaging techniques used to diagnose various diseases in the medical field.
no code implementations • ICCV 2023 • Kyungmin Jo, Wonjoon Jin, Jaegul Choo, Hyunjoon Lee, Sunghyun Cho
In this paper, we propose SideGAN, a novel 3D GAN training method to generate photo-realistic images irrespective of the camera pose, especially for faces of side-view angles.
no code implementations • 7 Dec 2021 • Kyungmin Jo, Gyumin Shim, Sanghun Jung, Soyoung Yang, Jaegul Choo
While recent NeRF-based generative models achieve the generation of diverse 3D-aware images, these approaches have limitations when generating images that contain user-specified characteristics.
no code implementations • 26 Nov 2020 • Jeonghoon Park, Kyungmin Jo, Daehoon Gwak, Jimin Hong, Jaegul Choo, Edward Choi
We evaluate the out-of-distribution (OOD) detection performance of self-supervised learning (SSL) techniques with a new evaluation framework.
Out-of-Distribution Detection Out of Distribution (OOD) Detection +1