🔥 Biography

I am a Postdoc at Nanyang Technological University, working with Prof. Yang Liu. I received my Ph.D. Degree from University of Chinese Academy of Sciences, advised by Professor Xiaochun Cao. My PhD research interests include computer vision, adversarial attack, adversarial training and reinforcement learning etc.

I was a visiting student (Remote) from February, 2023 to September, 2023 in the Torr Vision Group, University of Oxford, advised by Prof. Philip Torr. I was a research intern from March, 2022 to February, 2023 at Ali Group Security. I was a research intern from May, 2020 to February, 2022 at Tencent AI Lab.

At present, I am focused on issues related to the security of large models, including jailbreaking attacks on LLM (Large Language Models), adversarial transferability on VLM (Vision Language Models), and so on.

🎉 News

• 2024.04:   One paper on Survey on Transferability of Adversarial Examples is accepted in TMLR2024.
• 2024.04:   One paper on Fast Adversarial Training is accepted in TIFS2024.
• 2024.03:   One paper on Fast Adversarial Training is accepted in TPAMI2024.
• 2024.02:   One paper on Adversarial Attack on 3D is accepted in CVPR2024.
• 2024.01:   One paper on Backdoor Attack is accepted in ICLR2024.
• 2024.01:   One Journal paper on Backdoor Attack is accepted to TIFS2024.
• 2023.12:   Second runner-up in NeurIPS 2023 Red Teaming Track - Base Model Subtrack.
• 2023.12:   One paper on AI safety and robustness are accepted in AAAI2024.
• 2023.12:   One Journal paper on AI safety and robustness are accepted in IJCV2024.
• 2023.10:   One Journal paper on Fast Adversarial Training is accepted to TIFS2024.

📝 Publications

• A Survey on Transferability of Adversarial Examples Across Deep Neural Networks, Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqian Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip Torr, TMLR 2024 | Project | Github

• Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging, Xiaojun Jia, Yuefeng Chen, Xiaofeng Mao, Ranjie Duan, Jindong Gu, Rong Zhang, Hui Xue, Yang Liu, and Xiaochun Cao, TIFS 2024 | Project | Github

• Improving Fast Adversarial Training with Prior-Guided Knowledge, Xiaojun Jia, Yong Zhang, Xingxing Wei, Baoyuan Wu, Ke Ma, Jue Wang, and Xiaochun Cao, TPAMI 2024 | Project | Github

• Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point Clouds, Tianrui Lou, Xiaojun Jia(Corresponding Author), Jindong Gu, Li Liu, Siyuan Liang, Bangyan He, Xiaochun Cao, CVPR 2024 | Project | Github

• Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection, Jiawei Liang, Siyuan Liang, Aishan Liu, Xiaojun Jia, Junhao Kuang, Xiaochun Cao, ICLR 2024 | Project | Github

• Does Few-shot Learning Suffer from Backdoor Attacks?, Xinwei Liu, Xiaojun Jia(Corresponding Author), Jindong Gu, Yuan Xun, Siyuan Liang, Xiaochun Cao, AAAI 2024

• Context-Aware Robust Fine-Tuning, Xiaofeng Mao, Yufeng Chen, Xiaojun Jia, Rong Zhang, Hui Xue and Zhao Li, IJCV 2023

• Propagation is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetwork, Xiaojun Jia, Jianshu Li, Jindong Gu, Yang Bai and Xiaochun Cao, TIFS, 2023

• Hi-SIGIR: Hierachical Semantic-Guided Image-to-image Retrieval via Scene Graph, Yulu Wang, Pengwen Dai, Xiaojun Jia, Zhitao Zeng, Rui Li, Xiaochun Cao, ACM MM, 2023 | Project | Github

• Robust Automatic Speech Recognition via WavAugment Guided Phoneme Adversarial Training, Gege Qi, Yuefeng Chen, Xiaofeng Mao, Xiaojun Jia, Ranjie Duan, rong zhang, hui xue, INTERSPEECH 2023 | Project | Github

• Inequality phenomenon in adversarial training, and its unrealized threats, Ranjie Duan, YueFeng Chen, Yao Zhu, Xiaojun Jia, Rong Zhang, Hui Xue ICLR, 2023 | Project | Github

• Generating Transferable 3D Adversarial Point Cloud via Random Perturbation Factorization, Bangyan He, Jian Liu, Yiming Li, Siyuan Liang, Jingzhi Li, Xiaojun Jia(Corresponding Author), Xiaochun Cao AAAI, 2023 | Project | Github

• A Large-scale Multiple-objective Method for Black-box Attack against Object Detection, Siyuan Liang, Longkang Li, Yanbo Fan, Xiaojun Jia, Jingzhi Li, Baoyuan Wu, and Xiaochun Cao ECCV, 2022 | Project | Github

• Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal, Xinwei Liu, Jian Liu, Yang Bai, Jindong Gu, Tao Chen, Xiaojun Jia(Corresponding Author), Xiaochun Cao ECCV, 2022 | Project | Github

• Prior-Guided Adversarial Initialization for Fast Adversarial Training, Xiaojun Jia, Yong Zhang, Xingxing Wei, Baoyuan Wu, Ke Ma, Jue Wang, Xiaochun Cao ECCV, 2022 | Project | Github

• Boosting Fast Adversarial Training with Learnable Adversarial Initialization, Xiaojun Jia, Yong Zhang, Baoyuan Wu, Jue Wang, Xiaochun Cao TIP, 2022 | Project | Github

• LAS-AT: Adversarial Training with Learnable Attack Strategy(Oral), Xiaojun Jia, Yong Zhang, Baoyuan Wu, Ke Ma, Jue Wang, Xiaochun Cao CVPR(Oral), 2022 | Project | Github

• Defending against Model Stealing via Verifying Embedded External Features, Yiming Li, Linghui Zhu, Xiaojun Jia, Yong Jiang, Shu-Tao Xia, Xiaochun Cao AAAI, 2021 | Project | Github

• Adv-watermark: A novel watermark perturbation for adversarial examples, Xiaojun Jia, Xingxing Wei, Xiaochun Cao, Xiaoguang Han ACM MM, 2020 | Project | Github

• Comdefend: An efficient image compression model to defend adversarial examples, Xiaojun Jia, Xingxing Wei, Xiaochun Cao, Hassan Foroosh CVPR, 2019 | Project | Github

🎉 Professional Service

Reviewer: CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, AAAI, IJCAI, IEEE TPAMI, IEEE TIP, IEEE TIFS

🎖 Honors and Awards

• 2023.12.18 NeurIPS 2023 Red Teaming Track - Base Model Subtrack, Second runner-up.
• 2021.06 ACM MM2021 Security AI Challenger: Robust Logo Detection, Runner-up.
• 2021.11 Face security confrontation in OPPO Security Challenge, Runner-up.
• 2021 Best Paper of Adversarial for Good Award, ICML AdvML Workshop.

📖 Educations

• 2023.08 - now Nanyang Technological University, Research Fellow.
• 2018.06 - 2023.07 School of Cyberspace Security, University of Chinese Academy of Sciences, PhD.
• 2014.09 - 2018.06, School of Information Engineering, China University of Geosciences, Bachelor.

💬 Invited Talks

• 2022.11, Department of Electronic Engineering,Tsinghua University. | Slide
• 2022.11, Huawei Shield Lab. | Slide
• 2022.07, Institute of Information Engineering, University of Chinese Academy of Sciences. | Slide
• 2022.06, AI Drive. | Slide
• 2022.06, 机器之心synced. | Slide
• 2022.03, School of Computer Science, China University of Geosciences. | Slide

💻 Internships

• 2020.05 - 2022.02, Research Intern, Tencent AI Lab, Tencent, China.
• 2022.03 - Up to now, Research Intern, Ali Group Security, China.