Search Results for author: Zihao Xiao

Found 8 papers, 0 papers with code

Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition

no code implementations9 Mar 2022 Xiao Yang, Yinpeng Dong, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu

It is therefore imperative to develop a framework that can enable a comprehensive evaluation of the vulnerability of face recognition in the physical world.

3D FACE MODELING Face Recognition

Improving Transferability of Adversarial Patches on Face Recognition with Generative Models

no code implementations CVPR 2021 Zihao Xiao, Xianfeng Gao, Chilin Fu, Yinpeng Dong, Wei Gao, Xiaolu Zhang, Jun Zhou, Jun Zhu

However, deep CNNs are vulnerable to adversarial patches, which are physically realizable and stealthy, raising new security concerns on the real-world applications of these models.

Face Recognition

Black-box Detection of Backdoor Attacks with Limited Information and Data

no code implementations ICCV 2021 Yinpeng Dong, Xiao Yang, Zhijie Deng, Tianyu Pang, Zihao Xiao, Hang Su, Jun Zhu

Although deep neural networks (DNNs) have made rapid progress in recent years, they are vulnerable in adversarial environments.

Benchmarking Adversarial Robustness

no code implementations26 Dec 2019 Yinpeng Dong, Qi-An Fu, Xiao Yang, Tianyu Pang, Hang Su, Zihao Xiao, Jun Zhu

Deep neural networks are vulnerable to adversarial examples, which becomes one of the most important research problems in the development of deep learning.

Adversarial Attack Adversarial Robustness +1

DASZL: Dynamic Action Signatures for Zero-shot Learning

no code implementations8 Dec 2019 Tae Soo Kim, Jonathan D. Jones, Michael Peven, Zihao Xiao, Jin Bai, Yi Zhang, Weichao Qiu, Alan Yuille, Gregory D. Hager

There are many realistic applications of activity recognition where the set of potential activity descriptions is combinatorially large.

Action Detection Activity Detection +3

RSA: Randomized Simulation as Augmentation for Robust Human Action Recognition

no code implementations3 Dec 2019 Yi Zhang, Xinyue Wei, Weichao Qiu, Zihao Xiao, Gregory D. Hager, Alan Yuille

In this paper, we propose the Randomized Simulation as Augmentation (RSA) framework which augments real-world training data with synthetic data to improve the robustness of action recognition networks.

Action Recognition

Towards Training Probabilistic Topic Models on Neuromorphic Multi-chip Systems

no code implementations10 Apr 2018 Zihao Xiao, Jianfei Chen, Jun Zhu

We also propose an extension to train pLSI and a method to prune the network to obey the limited fan-in of some NMSs.

Stochastic Optimization Topic Models

Cannot find the paper you are looking for? You can Submit a new open access paper.