no code implementations • 27 Jun 2023 • Hong Joo Lee, Yong Man Ro
With the class-wise robust features, the model explicitly learns adversarially robust features through the proposed robust proxy learning framework.
no code implementations • 27 Jun 2023 • Hong Joo Lee, Youngjoon Yu, Yong Man Ro
Different from the previous approaches, in this paper, we propose a new approach to improve the adversarial robustness by using an external signal rather than model parameters.
no code implementations • 27 Apr 2022 • Youngjoon Yu, Hong Joo Lee, Hakmin Lee, Yong Man Ro
Person detection has attracted great attention in the computer vision area and is an imperative element in human-centric computer vision.
no code implementations • CVPR 2020 • Hong Joo Lee, Jung Uk Kim, Sangmin Lee, Hak Gu Kim, Yong Man Ro
We demonstrate that the proposed method could surpass the state-of-the-art segmentation network and improve the accuracy of three different segmentation network models on different types of medical image datasets.
no code implementations • 22 May 2020 • Youngjoon Yu, Hong Joo Lee, Byeong Cheon Kim, Jung Uk Kim, Yong Man Ro
The success of multimodal data fusion in deep learning appears to be attributed to the use of complementary in-formation between multiple input data.
no code implementations • 21 May 2020 • Hong Joo Lee, Seong Tae Kim, Hakmin Lee, Nassir Navab, Yong Man Ro
Experimental results show that the proposed method could provide useful uncertainty information by Bayesian approximation with the efficient ensemble model generation and improve the predictive performance.
no code implementations • 21 May 2020 • Hakmin Lee, Hong Joo Lee, Seong Tae Kim, Yong Man Ro
After the ensemble models are trained, it can hide the gradient efficiently and avoid the gradient-based attack by the random layer sampling method.