no code implementations • 25 Oct 2022 • Youngin Cho, Junsoo Lee, Soyoung Yang, Juntae Kim, Yeojeong Park, Haneol Lee, Mohammad Azam Khan, Daesik Kim, Jaegul Choo
Existing deep interactive colorization models have focused on ways to utilize various types of interactions, such as point-wise color hints, scribbles, or natural-language texts, as methods to reflect a user's intent at runtime.
no code implementations • 25 Oct 2022 • Youngin Cho, Daejin Kim, Dongmin Kim, Mohammad Azam Khan, Jaegul Choo
Time series forecasting has become a critical task due to its high practicality in real-world applications such as traffic, energy consumption, economics and finance, and disease analysis.
no code implementations • 12 Jun 2022 • Youngin Cho, Daejin Kim, Mohammad Azam Khan, Jaegul Choo
Therefore, in this study we explore the practical setting called the single positive setting, where each data instance is annotated by only one positive label with no explicit negative labels.
no code implementations • CVPR 2021 • Daejin Kim, Mohammad Azam Khan, Jaegul Choo
While the existing cycle-consistency loss ensures that the image can be translated back, our approach makes the model further preserve the attribute-irrelevant regions even in a single translation to another domain by using the Grad-CAM output computed from the discriminator.
no code implementations • ACL 2021 • Cheonbok Park, Yunwon Tae, Taehee Kim, Soyoung Yang, Mohammad Azam Khan, Eunjeong Park, Jaegul Choo
To address this issue, this paper presents a novel meta-learning algorithm for unsupervised neural machine translation (UNMT) that trains the model to adapt to another domain by utilizing only a small amount of training data.
1 code implementation • arXiv.org 2020 • Seokwoo Jung, Sungha Choi, Mohammad Azam Khan, Jaegul Choo
This paper addresses the problem that pixel embedding in proposal-free instance segmentation based lane detection is difficult to optimize.
Ranked #10 on Lane Detection on TuSimple