no code implementations • 18 Mar 2024 • Seungbeom Woo, Geonwoo Baek, TaeHoon Kim, Jaemin Na, Joong-won Hwang, Wonjun Hwang
This framework dynamically cycles through multiple target domains, aligning each domain individually to restrain the biased alignment problem, and utilizes Fisher information to minimize the forgetting of knowledge from previous target domains.
no code implementations • 21 Sep 2020 • Joong-won Hwang, Youngwan Lee, Sungchan Oh, Yuseok Bae
Moreover, we further improved SWA to be adequate to adversarial training.
no code implementations • 28 Jun 2020 • Youngwan Lee, Joong-won Hwang, Hyung-Il Kim, Kimin Yun, Yongjin Kwon, Yuseok Bae, Sung Ju Hwang
To tackle these limitations, we propose a new localization uncertainty estimation method called UAD for anchor-free object detection.
Ranked #116 on Object Detection on COCO test-dev
14 code implementations • 22 Apr 2019 • Youngwan Lee, Joong-won Hwang, Sangrok Lee, Yuseok Bae, Jongyoul Park
As DenseNet conserves intermediate features with diverse receptive fields by aggregating them with dense connection, it shows good performance on the object detection task.
Ranked #64 on Instance Segmentation on COCO test-dev
no code implementations • 1 Dec 2017 • Seung-Hwan Bae, Youngwan Lee, Youngjoo Jo, Yuseok Bae, Joong-won Hwang
The recent advances of convolutional detectors show impressive performance improvement for large scale object detection.