no code implementations • 11 Apr 2022 • Jungbeom Lee, Eunji Kim, Jisoo Mok, Sungroh Yoon
This manipulation is realized in an anti-adversarial manner, so that the original image is perturbed along pixel gradients in directions opposite to those used in an adversarial attack.
1 code implementation • CVPR 2022 • Jisoo Mok, Byunggook Na, Ji-Hoon Kim, Dongyoon Han, Sungroh Yoon
To take such non-linear characteristics into account, we introduce Label-Gradient Alignment (LGA), a novel NTK-based metric whose inherent formulation allows it to capture the large amount of non-linear advantage present in modern neural architectures.
1 code implementation • 30 Jan 2022 • Byunggook Na, Jisoo Mok, Seongsik Park, Dongjin Lee, Hyeokjun Choe, Sungroh Yoon
We investigate the design choices used in the previous studies in terms of the accuracy and number of spikes and figure out that they are not best-suited for SNNs.
1 code implementation • NeurIPS 2021 • Jungbeom Lee, Jooyoung Choi, Jisoo Mok, Sungroh Yoon
Weakly supervised semantic segmentation produces pixel-level localization from class labels; however, a classifier trained on such labels is likely to focus on a small discriminative region of the target object.
Ranked #19 on Weakly-Supervised Semantic Segmentation on COCO 2014 val
Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation
1 code implementation • ICCV 2021 • Jisoo Mok, Byunggook Na, Hyeokjun Choe, Sungroh Yoon
Current efforts to improve the robustness of neural networks against adversarial examples are focused on developing robust training methods, which update the weights of a neural network in a more robust direction.
1 code implementation • 9 Jun 2021 • Byunggook Na, Jisoo Mok, Hyeokjun Choe, Sungroh Yoon
By analyzing proxy data constructed using various selection methods through data entropy, we propose a novel proxy data selection method tailored for NAS.