1 code implementation • ICCV 2023 • Hyunjae Lee, Heon Song, Hyeonsoo Lee, Gi-hyeon Lee, Suyeong Park, Donggeun Yoo
On the other hand, Self-Distillation (SD) only transfers partial knowledge learned by the task model itself.
no code implementations • CVPR 2023 • Jeongun Ryu, Aaron Valero Puche, Jaewoong Shin, Seonwook Park, Biagio Brattoli, Jinhee Lee, Wonkyung Jung, Soo Ick Cho, Kyunghyun Paeng, Chan-Young Ock, Donggeun Yoo, Sérgio Pereira
Cell detection is a fundamental task in computational pathology that can be used for extracting high-level medical information from whole-slide images.
no code implementations • CVPR 2023 • Mingu Kang, Heon Song, Seonwook Park, Donggeun Yoo, Sérgio Pereira
To address this need, we execute the largest-scale study of SSL pre-training on pathology image data, to date.
no code implementations • 26 Sep 2022 • Hyunjae Lee, Gihyeon Lee, Junhwan Kim, Sungjun Cho, Dohyun Kim, Donggeun Yoo
However, it often results in selecting a sub-optimal configuration as training with the high-performing configuration typically converges slowly in an early phase.
1 code implementation • CVPR 2022 • Chunggi Lee, Seonwook Park, Heon Song, Jeongun Ryu, Sanghoon Kim, Haejoon Kim, Sérgio Pereira, Donggeun Yoo
We perform experiments on the Tiny-DOTA and LCell datasets using both two-stage and one-stage object detection architectures to verify the efficacy of our approach.
2 code implementations • ECCV 2020 • Minchul Kim, Jongchan Park, Seil Na, Chang Min Park, Donggeun Yoo
Current methods for solving this task exploit various characteristics of the chest X-ray image, but one of the most important characteristics is still missing: the necessity of comparison between related regions in an image.
3 code implementations • CVPR 2021 • Hyeonseob Nam, Hyunjae Lee, Jongchan Park, Wonjun Yoon, Donggeun Yoo
Convolutional Neural Networks (CNNs) often fail to maintain their performance when they confront new test domains, which is known as the problem of domain shift.
Ranked #62 on Domain Generalization on PACS
no code implementations • 16 Sep 2019 • Seokju Lee, Junsik Kim, Tae-Hyun Oh, Yongseop Jeong, Donggeun Yoo, Stephen Lin, In So Kweon
We postulate that success on this task requires the network to learn semantic and geometric knowledge in the ego-centric view.
2 code implementations • 7 Jun 2019 • Inwan Yoo, Donggeun Yoo, Kyunghyun Paeng
In this paper, we propose a weakly supervised nuclei segmentation method, which requires only point annotations for training.
6 code implementations • CVPR 2019 • Donggeun Yoo, In So Kweon
In this paper, we propose a novel active learning method that is simple but task-agnostic, and works efficiently with the deep networks.
Ranked #3 on Active Learning on CIFAR10 (10,000)
no code implementations • CVPR 2018 • Jongchan Park, Joon-Young Lee, Donggeun Yoo, In So Kweon
In addition, we present a 'distort-and-recover' training scheme which only requires high-quality reference images for training instead of input and retouched image pairs.
no code implementations • 6 Feb 2018 • Dahun Kim, Donghyeon Cho, Donggeun Yoo, In So Kweon
The recovery of the aforementioned damage pushes the network to obtain robust and general-purpose representations.
1 code implementation • PSIVT 2017 • Oleksandr Bogdan, Oleg Yurchenko, Oleksandr Bailo, Francois Rameau, Donggeun Yoo, In So Kweon
This paper proposes a wearable system for visually impaired people that can be utilized to obtain an extensive feedback about their surrounding environment.
no code implementations • ICCV 2017 • Dahun Kim, Donghyeon Cho, Donggeun Yoo, In So Kweon
Weakly supervised semantic segmentation and localiza- tion have a problem of focusing only on the most important parts of an image since they use only image-level annota- tions.
no code implementations • 20 Dec 2016 • Donggeun Yoo, Sunggyun Park, Kyunghyun Paeng, Joon-Young Lee, In So Kweon
In this paper, we present an "action-driven" detection mechanism using our "top-down" visual attention model.
1 code implementation • 24 Mar 2016 • Donggeun Yoo, Namil Kim, Sunggyun Park, Anthony S. Paek, In So Kweon
We present an image-conditional image generation model.
no code implementations • ICCV 2015 • Donggeun Yoo, Sunggyun Park, Joon-Young Lee, Anthony S. Paek, In So Kweon
We present a novel detection method using a deep convolutional neural network (CNN), named AttentionNet.
no code implementations • 4 Dec 2014 • Donggeun Yoo, Sunggyun Park, Joon-Young Lee, In So Kweon
In this paper, we present a straightforward framework for better image representation by combining the two approaches.