no code implementations • ICCV 2023 • Wenkai Dong, Song Xue, Xiaoyue Duan, Shumin Han
This technique ensures a superior trade-off between editability and high fidelity to the input image of our method.
no code implementations • 28 Nov 2022 • Xiaoyue Duan, Guoliang Kang, Runqi Wang, Shumin Han, Song Xue, Tian Wang, Baochang Zhang
Based on this observation, we propose a simple strategy, i. e., increasing the number of training shots, to mitigate the loss of intrinsic dimension caused by robustness-promoting regularization.
no code implementations • 28 Dec 2021 • Runqi Wang, Xiaoyue Duan, Baochang Zhang, Song Xue, Wentao Zhu, David Doermann, Guodong Guo
We show that our method improves the recognition accuracy of adversarial training on ImageNet by 8. 32% compared with the baseline.
no code implementations • ICCV 2021 • Song Xue, Runqi Wang, Baochang Zhang, Tian Wang, Guodong Guo, David Doermann
Differentiable Architecture Search (DARTS) improves the efficiency of architecture search by learning the architecture and network parameters end-to-end.
no code implementations • ECCV 2020 • Hanlin Chen, Baochang Zhang, Song Xue, Xuan Gong, Hong Liu, Rongrong Ji, David Doermann
Deep convolutional neural networks (DCNNs) have dominated as the best performers in machine learning, but can be challenged by adversarial attacks.