1 code implementation • 30 May 2024 • Jaerin Lee, Bong Gyun Kang, Kihoon Kim, Kyoung Mu Lee
One puzzling artifact in machine learning dubbed grokking is where delayed generalization is achieved tenfolds of iterations after near perfect overfitting to the training data.
2 code implementations • 14 Mar 2024 • Jaerin Lee, Daniel Sungho Jung, Kanggeon Lee, Kyoung Mu Lee
The enormous success of diffusion models in text-to-image synthesis has made them promising candidates for the next generation of end-user applications for image generation and editing.
no code implementations • 5 Feb 2024 • Jaerin Lee, JoonKyu Park, Sungyong Baik, Kyoung Mu Lee
Image restoration models are typically trained with a pixel-wise distance loss defined over the RGB color representation space, which is well known to be a source of blurry and unrealistic textures in the restored images.
no code implementations • 22 Nov 2023 • JaeYoung Chung, Suyoung Lee, Hyeongjin Nam, Jaerin Lee, Kyoung Mu Lee
Specifically, we project a portion of point cloud to the desired view and provide the projection as a guidance for inpainting using the generative model.
no code implementations • ICLR 2022 • Seungjun Nah, Sanghyun Son, Jaerin Lee, Kyoung Mu Lee
The supervised reblurring loss at training stage compares the amplified blur between the deblurred and the sharp images.
no code implementations • 1 Jan 2021 • Jaerin Lee, Kyoung Mu Lee
Mini-batch SGD is a predominant optimization method in deep learning.
no code implementations • 28 Sep 2020 • Sanghyun Son, Jaerin Lee, Seungjun Nah, Radu Timofte, Kyoung Mu Lee
Videos in the real-world contain various dynamics and motions that may look unnaturally discontinuous in time when the recordedframe rate is low.