Search Results for author: Xiaofei Xie

Found 31 papers, 5 papers with code

Learning to Adversarially Blur Visual Object Tracking

no code implementations26 Jul 2021 Qing Guo, Ziyi Cheng, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yang Liu, Jianjun Zhao

In this work, we explore the robustness of visual object trackers against motion blur from a new angle, i. e., adversarial blur attack (ABA).

Visual Object Tracking Visual Tracking

Cross-Lingual Adaptation for Type Inference

no code implementations1 Jul 2021 Zhiming Li, Xiaofei Xie, Haoliang Li, Zhengzi Xu, Yi Li, Yang Liu

In this paper, we propose cross-lingual adaptation of program analysis, which allows us to leverage prior knowledge learned from the labeled dataset of one language and transfer it to the others.

Code Summarization Cross-Lingual Transfer +2

AVA: Adversarial Vignetting Attack against Visual Recognition

no code implementations12 May 2021 Binyu Tian, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Xiaohong Li, Yang Liu

Moreover, we propose the geometry-aware level-set optimization method to solve the adversarial vignetting regions and physical parameters jointly.

Independent Reinforcement Learning for Weakly Cooperative Multiagent Traffic Control Problem

1 code implementation22 Apr 2021 Chengwei Zhang, Shan Jin, Wanli Xue, Xiaofei Xie, ShengYong Chen, Rong Chen

To this, we model the traffic control problem as a partially observable weak cooperative traffic model (PO-WCTM) to optimize the overall traffic situation of a group of intersections.

Decision Making

Neuron Coverage-Guided Domain Generalization

no code implementations27 Feb 2021 Chris Xing Tian, Haoliang Li, Xiaofei Xie, Yang Liu, Shiqi Wang

More specifically, by treating the DNN as a program and each neuron as a functional point of the code, during the network training we aim to improve the generalization capability by maximizing the neuron coverage of DNN with the gradient similarity regularization between the original and augmented samples.

Domain Generalization

Sparta: Spatially Attentive and Adversarially Robust Activations

no code implementations1 Jan 2021 Qing Guo, Felix Juefei-Xu, Changqing Zhou, Lei Ma, Xiaofei Xie, Wei Feng, Yang Liu

Moreover, comprehensive evaluations have demonstrated two important properties of our method: First, superior transferability across DNNs.


It's Raining Cats or Dogs? Adversarial Rain Attack on DNN Perception

no code implementations19 Sep 2020 Liming Zhai, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Lei Ma, Wei Feng, Shengchao Qin, Yang Liu

With this generator, we further propose the adversarial rain attack against the image classification and object detection, where the rain factors are guided by the various DNNs.

Adversarial Attack Autonomous Driving +3

Bias Field Poses a Threat to DNN-based X-Ray Recognition

no code implementations19 Sep 2020 Binyu Tian, Qing Guo, Felix Juefei-Xu, Wen Le Chan, Yupeng Cheng, Xiaohong Li, Xiaofei Xie, Shengchao Qin

Our method reveals the potential threat to the DNN-based X-ray automated diagnosis and can definitely benefit the development of bias-field-robust automated diagnosis system.

Adversarial Attack

Adversarial Exposure Attack on Diabetic Retinopathy Imagery

no code implementations19 Sep 2020 Yupeng Cheng, Felix Juefei-Xu, Qing Guo, Huazhu Fu, Xiaofei Xie, Shang-Wei Lin, Weisi Lin, Yang Liu

In this paper, we study this problem from the viewpoint of adversarial attack and identify a totally new task, i. e., adversarial exposure attack generating adversarial images by tuning image exposure to mislead the DNNs with significantly high transferability.

Adversarial Attack

EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining

1 code implementation19 Sep 2020 Qing Guo, Jingyang Sun, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Wei Feng, Yang Liu

To fill this gap, in this paper, we regard the single-image deraining as a general image-enhancing problem and originally propose a model-free deraining method, i. e., EfficientDeRain, which is able to process a rainy image within 10~ms (i. e., around 6~ms on average), over 80 times faster than the state-of-the-art method (i. e., RCDNet), while achieving similar de-rain effects.

Data Augmentation Single Image Deraining

FakeRetouch: Evading DeepFakes Detection via the Guidance of Deliberate Noise

no code implementations19 Sep 2020 Yihao Huang, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Lei Ma, Weikai Miao, Yang Liu, Geguang Pu

Thus we use a combination of additive noise and deep image filtering to reconstruct the fake images, and we name our method FakeRetouch.

DeepFake Detection Face Swapping +1

Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems

no code implementations15 Sep 2020 Haoliang Li, Yufei Wang, Xiaofei Xie, Yang Liu, Shiqi Wang, Renjie Wan, Lap-Pui Chau, Alex C. Kot

In this paper, we propose a novel black-box backdoor attack technique on face recognition systems, which can be conducted without the knowledge of the targeted DNN model.

Face Recognition

Can We Trust Your Explanations? Sanity Checks for Interpreters in Android Malware Analysis

no code implementations13 Aug 2020 Ming Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu

For this reason, a variety of explanation approaches are proposed to interpret predictions by providing important features.

Cryptography and Security Software Engineering

FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction

no code implementations13 Jun 2020 Yihao Huang, Felix Juefei-Xu, Run Wang, Qing Guo, Lei Ma, Xiaofei Xie, Jianwen Li, Weikai Miao, Yang Liu, Geguang Pu

At this moment, GAN-based image generation methods are still imperfect, whose upsampling design has limitations in leaving some certain artifact patterns in the synthesized image.

DeepFake Detection Face Swapping +2

DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms

no code implementations13 Jun 2020 Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Wei Feng, Yang Liu, Jianjun Zhao

As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand for effective DeepFakes detectors.

DeepFake Detection Face Swapping +2

Stealing Deep Reinforcement Learning Models for Fun and Profit

no code implementations9 Jun 2020 Kangjie Chen, Shangwei Guo, Tianwei Zhang, Xiaofei Xie, Yang Liu

This paper presents the first model extraction attack against Deep Reinforcement Learning (DRL), which enables an external adversary to precisely recover a black-box DRL model only from its interaction with the environment.

Decision Making Imitation Learning +1

Retrieval-Augmented Generation for Code Summarization via Hybrid GNN

1 code implementation ICLR 2021 Shangqing Liu, Yu Chen, Xiaofei Xie, JingKai Siow, Yang Liu

However, automatic code summarization is challenging due to the complexity of the source code and the language gap between the source code and natural language summaries.

Code Summarization Source Code Summarization

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

no code implementations14 May 2020 Jianwen Sun, Tianwei Zhang, Xiaofei Xie, Lei Ma, Yan Zheng, Kangjie Chen, Yang Liu

Adversarial attacks against conventional Deep Learning (DL) systems and algorithms have been widely studied, and various defenses were proposed.

Adversarial Attack

Towards Characterizing Adversarial Defects of Deep Learning Software from the Lens of Uncertainty

no code implementations24 Apr 2020 Xiyue Zhang, Xiaofei Xie, Lei Ma, Xiaoning Du, Qiang Hu, Yang Liu, Jianjun Zhao, Meng Sun

Based on this, we propose an automated testing technique to generate multiple types of uncommon AEs and BEs that are largely missed by existing techniques.

Adversarial Attack

Towards Byzantine-resilient Learning in Decentralized Systems

no code implementations20 Feb 2020 Shangwei Guo, Tianwei Zhang, Xiaofei Xie, Lei Ma, Tao Xiang, Yang Liu

However, there are currently no satisfactory solutions with strong efficiency and security in decentralized systems.


FakeLocator: Robust Localization of GAN-Based Face Manipulations

no code implementations27 Jan 2020 Yihao Huang, Felix Juefei-Xu, Run Wang, Qing Guo, Xiaofei Xie, Lei Ma, Jianwen Li, Weikai Miao, Yang Liu, Geguang Pu

To the best of our knowledge, this is the very first attempt to solve the GAN-based fake localization problem with a gray-scale fakeness prediction map that preserves more information of fake regions.

Face Generation Semantic Segmentation

Amora: Black-box Adversarial Morphing Attack

no code implementations9 Dec 2019 Run Wang, Felix Juefei-Xu, Qing Guo, Yihao Huang, Xiaofei Xie, Lei Ma, Yang Liu

In this paper, we investigate and introduce a new type of adversarial attack to evade FR systems by manipulating facial content, called \textbf{\underline{a}dversarial \underline{mor}phing \underline{a}ttack} (a. k. a.

Adversarial Attack Dictionary Learning +3

SPARK: Spatial-aware Online Incremental Attack Against Visual Tracking

1 code implementation ECCV 2020 Qing Guo, Xiaofei Xie, Felix Juefei-Xu, Lei Ma, Zhongguo Li, Wanli Xue, Wei Feng, Yang Liu

We identify that online object tracking poses two new challenges: 1) it is difficult to generate imperceptible perturbations that can transfer across frames, and 2) real-time trackers require the attack to satisfy a certain level of efficiency.

Adversarial Attack Video Object Tracking +2

An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms

no code implementations15 Sep 2019 Qianyu Guo, Sen Chen, Xiaofei Xie, Lei Ma, Qiang Hu, Hongtao Liu, Yang Liu, Jianjun Zhao, Xiaohong Li

However, the differences in architecture designs and implementations of existing frameworks and platforms bring new challenges for DL software development and deployment.

Adversarial Attack Quantization

FakeSpotter: A Simple yet Robust Baseline for Spotting AI-Synthesized Fake Faces

no code implementations13 Sep 2019 Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, Yang Liu

In recent years, generative adversarial networks (GANs) and its variants have achieved unprecedented success in image synthesis.

Face Detection Face Recognition +2

DeepCruiser: Automated Guided Testing for Stateful Deep Learning Systems

no code implementations13 Dec 2018 Xiaoning Du, Xiaofei Xie, Yi Li, Lei Ma, Jianjun Zhao, Yang Liu

Our in-depth evaluation on a state-of-the-art speech-to-text DL system demonstrates the effectiveness of our technique in improving quality and reliability of stateful DL systems.

An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms

no code implementations13 Nov 2018 Qianyu Guo, Xiaofei Xie, Lei Ma, Qiang Hu, Ruitao Feng, Li Li, Yang Liu, Jianjun Zhao, Xiaohong Li

Up to the present, it still lacks a comprehensive study on how current diverse DL frameworks and platforms influence the DL software development process.

Autonomous Driving

Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer

no code implementations7 Sep 2018 Alvin Chan, Lei Ma, Felix Juefei-Xu, Xiaofei Xie, Yang Liu, Yew Soon Ong

Deep neural networks (DNN), while becoming the driving force of many novel technology and achieving tremendous success in many cutting-edge applications, are still vulnerable to adversarial attacks.

Question Answering

DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing

no code implementations4 Sep 2018 Xiaofei Xie, Lei Ma, Felix Juefei-Xu, Hongxu Chen, Minhui Xue, Bo Li, Yang Liu, Jianjun Zhao, Jianxiong Yin, Simon See

In company with the data explosion over the past decade, deep neural network (DNN) based software has experienced unprecedented leap and is becoming the key driving force of many novel industrial applications, including many safety-critical scenarios such as autonomous driving.

Autonomous Driving Quantization

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