no code implementations • 2 Nov 2023 • Jiwan Hur, Jaehyun Choi, Gyojin Han, Dong-Jae Lee, Junmo Kim
Training diffusion models on limited datasets poses challenges in terms of limited generation capacity and expressiveness, leading to unsatisfactory results in various downstream tasks utilizing pretrained diffusion models, such as domain translation and text-guided image manipulation.
1 code implementation • 20 Jul 2023 • Anita Rau, Sophia Bano, Yueming Jin, Pablo Azagra, Javier Morlana, Edward Sanderson, Bogdan J. Matuszewski, Jae Young Lee, Dong-Jae Lee, Erez Posner, Netanel Frank, Varshini Elangovan, Sista Raviteja, Zhengwen Li, Jiquan Liu, Seenivasan Lalithkumar, Mobarakol Islam, Hongliang Ren, José M. M. Montiel, Danail Stoyanov
We show that depth prediction in virtual colonoscopy is robustly solvable, while pose estimation remains an open research question.
no code implementations • 2 Jul 2023 • Gyojin Han, Dong-Jae Lee, Jiwan Hur, Jaehyun Choi, Junmo Kim
The proposed framework employs INRs to represent the secret data, which can handle data of various modalities and resolutions.
no code implementations • 9 Jun 2023 • Dong-Jae Lee, Jae Young Lee, Hyounguk Shon, Eojindl Yi, Yeong-Hun Park, Sung-Sik Cho, Junmo Kim
While most lightweight monocular depth estimation methods have been developed using convolution neural networks, the Transformer has been gradually utilized in monocular depth estimation recently.