Aishan Liu

According to our database, Aishan Liu authored at least 91 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Generate Transferable Adversarial Physical Camouflages via Triplet Attention Suppression.

Jiakai Wang, Xianglong Liu, Zixin Yin, Yuxuan Wang, Jun Guo, Haotong Qin, Qingtao Wu, Aishan Liu

Int. J. Comput. Vis., November, 2024

Towards Defending Multiple ℓ _p-Norm Bounded Adversarial Perturbations via Gated Batch Normalization.

Aishan Liu, Shiyu Tang, Xinyun Chen, Lei Huang, Haotong Qin, Xianglong Liu, Dacheng Tao

Int. J. Comput. Vis., June, 2024

Faire: Repairing Fairness of Neural Networks via Neuron Condition Synthesis.

Tianlin Li, Xiaofei Xie, Jian Wang, Qing Guo, Aishan Liu, Lei Ma, Yang Liu

ACM Trans. Softw. Eng. Methodol., January, 2024

Improving Deepfake Detection Generalization by Invariant Risk Minimization.

Zixin Yin, Jiakai Wang, Yisong Xiao, Hanqing Zhao, Tianlin Li, Wenbo Zhou, Aishan Liu, Xianglong Liu

IEEE Trans. Multim., 2024

Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection.

Simin Li, Huangxinxin Xu, Jiakai Wang, Ruixiao Xu, Aishan Liu, Fazhi He, Xianglong Liu, Dacheng Tao

IEEE Trans. Image Process., 2024

LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment.

Ge Yang, Changyi He, Jinyang Guo, Jianyu Wu, Yifu Ding, Aishan Liu, Haotong Qin, Pengliang Ji, Xianglong Liu

CoRR, 2024

SafeBench: A Safety Evaluation Framework for Multimodal Large Language Models.

Zonghao Ying, Aishan Liu, Siyuan Liang, Lei Huang, Jinyang Guo, Wenbo Zhou, Xianglong Liu, Dacheng Tao

CoRR, 2024

Module-wise Adaptive Adversarial Training for End-to-end Autonomous Driving.

Tianyuan Zhang, Lu Wang, Jiaqi Kang, Xinwei Zhang, Siyuan Liang, Yuwei Chen, Aishan Liu, Xianglong Liu

CoRR, 2024

Compromising Embodied Agents with Contextual Backdoor Attacks.

Aishan Liu, Yuguang Zhou, Xianglong Liu, Tianyuan Zhang, Siyuan Liang, Jiakai Wang, Yanjun Pu, Tianlin Li, Junqi Zhang, Wenbo Zhou, Qing Guo, Dacheng Tao

CoRR, 2024

GenderBias-VL: Benchmarking Gender Bias in Vision Language Models via Counterfactual Probing.

Yisong Xiao, Aishan Liu, QianJia Cheng, Zhenfei Yin, Siyuan Liang, Jiapeng Li, Jing Shao, Xianglong Liu, Dacheng Tao

CoRR, 2024

Revisiting Backdoor Attacks against Large Vision-Language Models.

Siyuan Liang, Jiawei Liang, Tianyu Pang, Chao Du, Aishan Liu, Ee-Chien Chang, Xiaochun Cao

CoRR, 2024

Unveiling the Safety of GPT-4o: An Empirical Study using Jailbreak Attacks.

Zonghao Ying, Aishan Liu, Xianglong Liu, Dacheng Tao

CoRR, 2024

Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt.

Zonghao Ying, Aishan Liu, Tianyuan Zhang, Zhengmin Yu, Siyuan Liang, Xianglong Liu, Dacheng Tao

CoRR, 2024

LanEvil: Benchmarking the Robustness of Lane Detection to Environmental Illusions.

Tianyuan Zhang, Lu Wang, Hainan Li, Yisong Xiao, Siyuan Liang, Aishan Liu, Xianglong Liu, Dacheng Tao

CoRR, 2024

Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography.

Nhat Minh Chung, Sensen Gao, Tuan-Anh Vu, Jie Zhang, Aishan Liu, Yun Lin, Jin Song Dong, Qing Guo

CoRR, 2024

Object Detectors in the Open Environment: Challenges, Solutions, and Outlook.

Siyuan Liang, Wei Wang, Ruoyu Chen, Aishan Liu, Boxi Wu, Ee-Chien Chang, Xiaochun Cao, Dacheng Tao

CoRR, 2024

Semantic Mirror Jailbreak: Genetic Algorithm Based Jailbreak Prompts Against Open-source LLMs.

Xiaoxia Li, Siyuan Liang, Jiyi Zhang, Han Fang, Aishan Liu, Ee-Chien Chang

CoRR, 2024

VL-Trojan: Multimodal Instruction Backdoor Attacks against Autoregressive Visual Language Models.

Jiawei Liang, Siyuan Liang, Man Luo, Aishan Liu, Dongchen Han, Ee-Chien Chang, Xiaochun Cao

CoRR, 2024

Transferable Multimodal Attack on Vision-Language Pre-training Models.

Haodi Wang, Kai Dong, Zhilei Zhu, Haotong Qin, Aishan Liu, Xiaolin Fang, Jiakai Wang, Xianglong Liu

Proceedings of the IEEE Symposium on Security and Privacy, 2024

Towards Robust Physical-world Backdoor Attacks on Lane Detection.

Xinwei Zhang, Aishan Liu, Tianyuan Zhang, Siyuan Liang, Xianglong Liu

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

PTSBench: A Comprehensive Post-Training Sparsity Benchmark Towards Algorithms and Models.

Zining Wang, Jinyang Guo, Ruihao Gong, Yang Yong, Aishan Liu, Yushi Huang, Jiaheng Liu, Xianglong Liu

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

<i>LanEvil</i>: Benchmarking the Robustness of Lane Detection to Environmental Illusions.

Tianyuan Zhang, Lu Wang, Hainan Li, Yisong Xiao, Siyuan Liang, Aishan Liu, Xianglong Liu, Dacheng Tao

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

RUNNER: Responsible UNfair NEuron Repair for Enhancing Deep Neural Network Fairness.

Tianlin Li, Yue Cao, Jian Zhang, Shiqian Zhao, Yihao Huang, Aishan Liu, Qing Guo, Yang Liu

Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection.

Jiawei Liang, Siyuan Liang, Aishan Liu, Xiaojun Jia, Junhao Kuang, Xiaochun Cao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game.

Simin Li, Jun Guo, Jingqiao Xiu, Ruixiao Xu, Xin Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

BadCLIP: Dual-Embedding Guided Backdoor Attack on Multimodal Contrastive Learning.

Siyuan Liang, Mingli Zhu, Aishan Liu, Baoyuan Wu, Xiaochun Cao, Ee-Chien Chang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

GenderCARE: A Comprehensive Framework for Assessing and Reducing Gender Bias in Large Language Models.

Kunsheng Tang, Wenbo Zhou, Jie Zhang, Aishan Liu, Gelei Deng, Shuai Li, Peigui Qi, Weiming Zhang, Tianwei Zhang, Nenghai Yu

Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024

2023

A comprehensive evaluation framework for deep model robustness.

Jun Guo, Wei Bao, Jiakai Wang, Yuqing Ma, Xinghai Gao, Gang Xiao, Aishan Liu, Jian Dong, Xianglong Liu, Wenjun Wu

Pattern Recognit., May, 2023

On the Guaranteed Almost Equivalence Between Imitation Learning From Observation and Demonstration.

Zhihao Cheng, Liu Liu, Aishan Liu, Hao Sun, Meng Fang, Dacheng Tao

IEEE Trans. Neural Networks Learn. Syst., February, 2023

RobustMQ: benchmarking robustness of quantized models.

Yisong Xiao, Aishan Liu, Tianyuan Zhang, Haotong Qin, Jinyang Guo, Xianglong Liu

Vis. Intell., 2023

Temporal Speciation Network for Few-Shot Object Detection.

Xiaowei Zhao, Xianglong Liu, Yuqing Ma, Shihao Bai, Yifan Shen, Zeyu Hao, Aishan Liu

IEEE Trans. Multim., 2023

Regionwise Generative Adversarial Image Inpainting for Large Missing Areas.

Yuqing Ma, Xianglong Liu, Shihao Bai, Lei Wang, Aishan Liu, Dacheng Tao, Edwin R. Hancock

IEEE Trans. Cybern., 2023

Pre-trained Trojan Attacks for Visual Recognition.

Aishan Liu, Xinwei Zhang, Yisong Xiao, Yuguang Zhou, Siyuan Liang, Jiakai Wang, Xianglong Liu, Xiaochun Cao, Dacheng Tao

CoRR, 2023

Adversarial Examples in the Physical World: A Survey.

Jiakai Wang, Donghua Wang, Jin Hu, Siyang Wu, Tingsong Jiang, Wen Yao, Aishan Liu, Xianglong Liu

CoRR, 2023

MIR2: Towards Provably Robust Multi-Agent Reinforcement Learning by Mutual Information Regularization.

Simin Li, Ruixiao Xu, Jun Guo, Pu Feng, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu, Weifeng Lv

CoRR, 2023

Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game.

Simin Li, Jun Guo, Jingqiao Xiu, Xini Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu

CoRR, 2023

Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks.

Simin Li, Shuing Zhang, Gujun Chen, Dong Wang, Pu Feng, Jiakai Wang, Aishan Liu, Xin Yi, Xianglong Liu

CoRR, 2023

Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence.

Simin Li, Jun Guo, Jingqiao Xiu, Pu Feng, Xin Yu, Jiakai Wang, Aishan Liu, Wenjun Wu, Xianglong Liu

CoRR, 2023

X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection.

Aishan Liu, Jun Guo, Jiakai Wang, Siyuan Liang, Renshuai Tao, Wenbo Zhou, Cong Liu, Xianglong Liu, Dacheng Tao

Proceedings of the 32nd USENIX Security Symposium, 2023

Exploring Inconsistent Knowledge Distillation for Object Detection with Data Augmentation.

Jiawei Liang, Siyuan Liang, Aishan Liu, Ke Ma, Jingzhi Li, Xiaochun Cao

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks.

Jun Guo, Xingyu Zheng, Aishan Liu, Siyuan Liang, Yisong Xiao, Yichao Wu, Xianglong Liu

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Face Encryption via Frequency-Restricted Identity-Agnostic Attacks.

Xin Dong, Rui Wang, Siyuan Liang, Aishan Liu, Lihua Jing

Proceedings of the 31st ACM International Conference on Multimedia, 2023

SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency.

Yan Wang, Yuhang Li, Ruihao Gong, Aishan Liu, Yanfei Wang, Jian Hu, Yongqiang Yao, Yunchen Zhang, Tianzi Xiao, Fengwei Yu, Xianglong Liu

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing.

Yisong Xiao, Aishan Liu, Tianlin Li, Xianglong Liu

Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2023

Fairness via Group Contribution Matching.

Tianlin Li, Zhiming Li, Anran Li, Mengnan Du, Aishan Liu, Qing Guo, Guozhu Meng, Yang Liu

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

FAIRER: Fairness as Decision Rationale Alignment.

Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li, Yang Liu

Proceedings of the International Conference on Machine Learning, 2023

Exploring the Relationship Between Architectural Design and Adversarially Robust Generalization.

Aishan Liu, Shiyu Tang, Siyuan Liang, Ruihao Gong, Boxi Wu, Xianglong Liu, Dacheng Tao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks.

Simin Li, Shuning Zhang, Gujun Chen, Dong Wang, Pu Feng, Jiakai Wang, Aishan Liu, Xin Yi, Xianglong Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Improving Robust Fariness via Balance Adversarial Training.

Chunyu Sun, Chenye Xu, Chengyuan Yao, Siyuan Liang, Yichao Wu, Ding Liang, Xianglong Liu, Aishan Liu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Universal Adversarial Patch Attack for Automatic Checkout Using Perceptual and Attentional Bias.

Jiakai Wang, Aishan Liu, Xiao Bai, Xianglong Liu

IEEE Trans. Image Process., 2022

Revisiting audio visual scene-aware dialog.

Aishan Liu, Huiyuan Xie, Xianglong Liu, Zixin Yin, Shunchang Liu

Neurocomputing, 2022

Exploring the Relationship between Architecture and Adversarially Robust Generalization.

Shiyu Tang, Siyuan Liang, Ruihao Gong, Aishan Liu, Xianglong Liu, Dacheng Tao

CoRR, 2022

Rethinking Data Augmentation in Knowledge Distillation for Object Detection.

Jiawei Liang, Siyuan Liang, Aishan Liu, Mingli Zhu, Danni Yuan, Chenye Xu, Xiaochun Cao

CoRR, 2022

Improving Robust Fairness via Balance Adversarial Training.

Chunyu Sun, Chenye Xu, Chengyuan Yao, Siyuan Liang, Yichao Wu, Ding Liang, Xianglong Liu, Aishan Liu

CoRR, 2022

Adaptive Perturbation Generation for Multiple Backdoors Detection.

Yuhang Wang, Huafeng Shi, Rui Min, Ruijia Wu, Siyuan Liang, Yichao Wu, Ding Liang, Aishan Liu

CoRR, 2022

Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection.

Simin Li, Huangxinxin Xu, Jiakai Wang, Aishan Liu, Fazhi He, Xianglong Liu, Dacheng Tao

CoRR, 2022

Generating Transferable Adversarial Examples against Vision Transformers.

Yuxuan Wang, Jiakai Wang, Zixin Yin, Ruihao Gong, Jingyi Wang, Aishan Liu, Xianglong Liu

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Few-shot X-ray Prohibited Item Detection: A Benchmark and Weak-feature Enhancement Network.

Renshuai Tao, Tianbo Wang, Ziyang Wu, Cong Liu, Aishan Liu, Xianglong Liu

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Imitated Detectors: Stealing Knowledge of Black-box Object Detectors.

Siyuan Liang, Aishan Liu, Jiawei Liang, Longkang Li, Yang Bai, Xiaochun Cao

Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

BiBERT: Accurate Fully Binarized BERT.

Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu

Proceedings of the Tenth International Conference on Learning Representations, 2022

Defensive Patches for Robust Recognition in the Physical World.

Jiakai Wang, Zixin Yin, Pengfei Hu, Aishan Liu, Renshuai Tao, Haotong Qin, Xianglong Liu, Dacheng Tao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Exploring Endogenous Shift for Cross-domain Detection: A Large-scale Benchmark and Perturbation Suppression Network.

Renshuai Tao, Hainan Li, Tianbo Wang, Yanlu Wei, Yifu Ding, Bowei Jin, Hongping Zhi, Xianglong Liu, Aishan Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Harnessing Perceptual Adversarial Patches for Crowd Counting.

Shunchang Liu, Jiakai Wang, Aishan Liu, Yingwei Li, Yijie Gao, Xianglong Liu, Dacheng Tao

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021

Interpreting and Improving Adversarial Robustness of Deep Neural Networks With Neuron Sensitivity.

Chongzhi Zhang, Aishan Liu, Xianglong Liu, Yitao Xu, Hang Yu, Yuqing Ma, Tianlin Li

IEEE Trans. Image Process., 2021

Progressive Diversified Augmentation for General Robustness of DNNs: A Unified Approach.

Hang Yu, Aishan Liu, Gengchao Li, Jichen Yang, Chongzhi Zhang

IEEE Trans. Image Process., 2021

Training Robust Deep Neural Networks via Adversarial Noise Propagation.

Aishan Liu, Xianglong Liu, Hang Yu, Chongzhi Zhang, Qiang Liu, Dacheng Tao

IEEE Trans. Image Process., 2021

Sequential alignment attention model for scene text recognition.

Yan Wu, Jiaxin Fan, Renshuai Tao, Jiakai Wang, Haotong Qin, Aishan Liu, Xianglong Liu

J. Vis. Commun. Image Represent., 2021

Understanding adversarial robustness via critical attacking route.

Tianlin Li, Aishan Liu, Xianglong Liu, Yitao Xu, Chongzhi Zhang, Xiaofei Xie

Inf. Sci., 2021

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques.

Shiyu Tang, Ruihao Gong, Yan Wang, Aishan Liu, Jiakai Wang, Xinyun Chen, Fengwei Yu, Xianglong Liu, Dawn Song, Alan L. Yuille, Philip H. S. Torr, Dacheng Tao

CoRR, 2021

Over-sampling De-occlusion Attention Network for Prohibited Items Detection in Noisy X-ray Images.

Renshuai Tao, Yanlu Wei, Hainan Li, Aishan Liu, Yifu Ding, Haotong Qin, Xianglong Liu

CoRR, 2021

A Comprehensive Evaluation Framework for Deep Model Robustness.

Aishan Liu, Xianglong Liu, Jun Guo, Jiakai Wang, Yuqing Ma, Ze Zhao, Xinghai Gao, Gang Xiao

CoRR, 2021

ADVM'21: 1st International Workshop on Adversarial Learning for Multimedia.

Aishan Liu, Xinyun Chen, Yingwei Li, Chaowei Xiao, Xun Yang, Xianglong Liu, Dawn Song, Dacheng Tao, Alan L. Yuille, Anima Anandkumar

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones.

Shan An, Guangfu Che, Jinghao Guo, Haogang Zhu, Junjie Ye, Fangru Zhou, Zhaoqi Zhu, Dong Wei, Aishan Liu, Wei Zhang

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World.

Jiakai Wang, Aishan Liu, Zixin Yin, Shunchang Liu, Shiyu Tang, Xianglong Liu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Boost System of Systems Modeling via UPDM: A Case Study from Air Traffic Management.

Huanhuan Shen, Weijie Zhu, Aishan Liu

Proceedings of the 4th International Conference on Complex Systems Design & Management Asia, 2021

A Deep Learning and Ontology Based Framework for Textual Requirements Analysis and Conceptual Model Generation.

Yongjun Qie, Huanhuan Shen, Aishan Liu

Proceedings of the 4th International Conference on Complex Systems Design & Management Asia, 2021

2020

Towards Defending Multiple Adversarial Perturbations via Gated Batch Normalization.

Aishan Liu, Shiyu Tang, Xianglong Liu, Xinyun Chen, Lei Huang, Zhuozhuo Tu, Dawn Song, Dacheng Tao

CoRR, 2020

Patch Attack for Automatic Check-out.

Aishan Liu, Jiakai Wang, Xianglong Liu, Chongzhi Zhang, Bowen Cao, Hang Yu

CoRR, 2020

Adversarial Attacks for Embodied Agents.

Aishan Liu, Tairan Huang, Xianglong Liu, Yitao Xu, Yuqing Ma, Xinyun Chen, Stephen J. Maybank, Dacheng Tao

CoRR, 2020

Dialogue Policies for Learning Board Games through Multimodal Communication.

Maryam Zare, Ali Ayub, Aishan Liu, Sweekar Sudhakara, Albert F. Wagner, Rebecca J. Passonneau

Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, 2020

Few-shot Visual Learning with Contextual Memory and Fine-grained Calibration.

Yuqing Ma, Wei Liu, Shihao Bai, Qingyu Zhang, Aishan Liu, Weimin Chen, Xianglong Liu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Transductive Relation-Propagation Network for Few-shot Learning.

Yuqing Ma, Shihao Bai, Shan An, Wei Liu, Aishan Liu, Xiantong Zhen, Xianglong Liu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Bias-Based Universal Adversarial Patch Attack for Automatic Check-Out.

Aishan Liu, Jiakai Wang, Xianglong Liu, Bowen Cao, Chongzhi Zhang, Hang Yu

Proceedings of the Computer Vision - ECCV 2020, 2020

Spatiotemporal Attacks for Embodied Agents.

Aishan Liu, Tairan Huang, Xianglong Liu, Yitao Xu, Yuqing Ma, Xinyun Chen, Stephen J. Maybank, Dacheng Tao

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Region-wise Generative Adversarial ImageInpainting for Large Missing Areas.

Yuqing Ma, Xianglong Liu, Shihao Bai, Lei Wang, Aishan Liu, Dacheng Tao, Edwin R. Hancock

CoRR, 2019

Training Robust Deep Neural Networks via Adversarial Noise Propagation.

Aishan Liu, Xianglong Liu, Chongzhi Zhang, Hang Yu, Qiang Liu, Junfeng He

CoRR, 2019

Interpreting and Improving Adversarial Robustness with Neuron Sensitivity.

Chongzhi Zhang, Aishan Liu, Xianglong Liu, Yitao Xu, Hang Yu, Yuqing Ma, Tianlin Li

CoRR, 2019

Towards Noise-Robust Neural Networks via Progressive Adversarial Training.

Hang Yu, Aishan Liu, Xianglong Liu, Jichen Yang, Chongzhi Zhang

CoRR, 2019

Coarse-to-Fine Image Inpainting via Region-wise Convolutions and Non-Local Correlation.

Yuqing Ma, Xianglong Liu, Shihao Bai, Lei Wang, Dailan He, Aishan Liu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Perceptual-Sensitive GAN for Generating Adversarial Patches.

Aishan Liu, Xianglong Liu, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie, Dacheng Tao

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2015

Automated Program Debugging for Multiple Bugs Based on Semantic Analysis.

Aishan Liu, Li Li, Jie Luo

Proceedings of the Structured Object-Oriented Formal Language and Method, 2015