no code implementations • 26 Feb 2023 • Byeonggeun Kim, Jun-Tae Lee, Seunghan Yang, Simyung Chang
Efficient transfer learning involves utilizing a pre-trained model trained on a larger dataset and repurposing it for downstream tasks with the aim of maximizing the reuse of the pre-trained model.
1 code implementation • ECCV 2020 • Dongkwon Jin, Jun-Tae Lee, Chang-Su Kim
A novel algorithm to detect semantic lines is proposed in this paper.
Ranked #2 on Line Detection on SEL
no code implementations • 29 Sep 2021 • Byeonggeun Kim, Seunghan Yang, Jangho Kim, Hyunsin Park, Jun-Tae Lee, Simyung Chang
While using two-dimensional convolutional neural networks (2D-CNNs) in image processing, it is possible to manipulate domain information using channel statistics, and instance normalization has been a promising way to get domain-invariant features.
no code implementations • ICLR 2021 • Jun-Tae Lee, Mihir Jain, Hyoungwoo Park, Sungrack Yun
Temporally localizing actions in videos is one of the key components for video understanding.
no code implementations • ICCV 2021 • HanUl Kim, Mihir Jain, Jun-Tae Lee, Sungrack Yun, Fatih Porikli
Efficient action recognition has become crucial to extend the success of action recognition to many real-world applications.
no code implementations • ICCV 2019 • Jun-Tae Lee, Chang-Su Kim
We propose a unified approach to three tasks of aesthetic score regression, binary aesthetic classification, and personalized aesthetics.
1 code implementation • ICCV 2017 • Jun-Tae Lee, Han-Ul Kim, Chul Lee, Chang-Su Kim
Then, we develop the line pooling layer to extract a feature vector for each candidate line from the feature maps.
Ranked #3 on Line Detection on SEL