Xianglong Liu


State Key Laboratory of Software Development Environment
School of Computer Science and Engineering, Beihang University, China

Office: Room G606, New Main Building
Address: 37 Xueyuan Road, Haidian, Beijing 100191, China
Tel.: +86-10-8233-8092
Email: xlliu@nlsde.buaa.edu.cn / xlliu@buaa.edu.cn

I am a Full Professor in School of Computer Science and Engineering at Beihang University. I received BS and Ph.D degrees under supervision of Prof. Wei Li, and visited DVMM Lab, Columbia University as a joint Ph.D student supervised by Prof. Shih-Fu Chang. My research interests include fast visual computing (e.g., large-scale search/understanding) and robust deep learning (e.g., network quantization, adversarial attack/defense, few shot learning). I received NSFC Excellent Young Scientists Fund, and was selected into 2019 Beijing Nova Program, MSRA StarTrack Program, and 2015 CCF Young Talents Development Program.

Our Group | AI Safety | Network Quantization | Open-World Detection

Selected Publications| All Publications | Hashing | Google Scholar | DBLP

  • NEW  Dec 2022: We are organizing 2nd workshop on Practical Deep Learning in the Wild with a Practical AI Challenge on AAAI 2023.
  • NEW  Sep 2022: Papers accepted by ACM CCS 2022, NeurIPS 2022 and IJCV respectively.
  • NEW  Jul 2022: Three papers accepted by ACM MM 2022 and Two papers accepted by ECCV 2022.
  • Mar 2022: Five papers about adversarial attack/defense and open-world object detection accepted by IEEE CVPR 2022.
  • Jan 2022: Two papers about BERT binarization and Low-bit Post-Training Quantization accepted by ICLR 2022.
  • Jan 2022: We are organizing IEEE CVPR 2022 workshop on The Art of Robustness: Devil and Angel in Adversarial Machine Learning
  • Oct 2021: We released the first comprehensive Robustness investigation benchmark (RobustART) on large-scale dataset ImageNet regarding ARchitectural design (44 human-designed off-the-shelf architectures and 1200+ neural architecture searched networks) and Training techniques (10+ general ones e.g., extra training data, etc) towards diverse noises (adversarial, natural, and system noises).
  • Oct 2021: Special Issue "Practical Deep Learning in the Wild" in Pattern Recognition (submission deadline: Nov, 2022).
  • Jul 2021: Welcome to our ACM MM workshop on Adversarial Learning for Multimedia and IJCAI workshop on Safety & Security of Deep Learning.
  • Jul 2021: Tutorial on Adversarial Examples for Deep Learning: Attack, Defense and Robustness, IEEE ICME 2021.

  • Selected Papers | AI Safety | Network Quantization | Open-World Detection | All Publications

    Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models
    Xiuying Wei, Yunchen Zhang, Xiangguo Zhang, Ruihao Gong, Shanghang Zhang, Qi Zhang, Fengwei Yu, Xianglong Liu*
    NeurIPS, 2022
    BiFSMN: Binary Neural Network for Keyword Spotting
    Haotong Qin, Xudong Ma, Yifu Ding, Xiaoyang Li, Yang Zhang, Yao Tian, Zejun Ma, Jie Luo, Xianglong Liu*
    IJCAI, 2022
    Defensive Patches for Robust Recognition in the Physical World
    Jiakai Wang, Zixin Yin, Pengfei Hu, Renshuai Tao, Haotong Qin, Xianglong Liu*, Dacheng Tao, Aishan Liu
    IEEE CVPR, 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
    IEEE CVPR, 2022
    QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization
    Xiuying Wei, Ruihao Gong, Yuhang Li, Xianglong Liu*, Fengwei Yu
    ICLR, 2022
    BiBERT: Accurate Fully Binarized BERT
    Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu*
    ICLR, 2022
    Towards Real-world X-ray Security Inspection: A High-quality Benchmark and Lateral Inhibition Module for Prohibited Items Detection
    Renshuai Tao, Yanlu Wei, Xiangjian Jiang, Hainan Li, Haotong Qin, Jiakai Wang, Yuqing Ma, Libo Zhang, Xianglong Liu*
    IEEE ICCV, 2021
    Dual Attention Suppression Attack: Generate Adversarial Camouflage in Physical World
    Jiakai Wang, Aishan Liu, Zixin Yin, Shunchang Liu, Shiyu Tang, Xianglong Liu*
    IEEE CVPR (oral), 2021
    Diversifying Sample Generation for Accurate Data-Free Quantization
    Xiangguo Zhang, Haotong Qin, Yifu Ding, Ruihao Gong, Qinghua Yan, Renshuai Tao, Yuhang Li, Fengwei Yu, Xianglong Liu*
    IEEE CVPR (oral), 2021
    BiPointNet: Binary Neural Network for Point Clouds
    Haotong Qin, Zhongang Cai, Mingyuan Zhang, Yifu Ding, Haiyu Zhao, Shuai Yi, Xianglong Liu*, Hao Su
    ICLR, 2021
    Bias-based Universal Adversarial Patch Attack for Automatic Check-out
    Aishan Liu, Jiakai Wang, Xianglong Liu*, Bowen Cao, Chongzhi Zhang, Hang Yu.
    ECCV, 2020
    Spatiotemporal Attacks for Embodied Agents
    Aishan Liu, Tairan Huang, Xianglong Liu, Yitao Xu, Yuqing Ma, Xinyun Chen, Stephen Maybank, Dacheng Tao
    ECCV, 2020
    Towards Unified INT8 Training for Convolutional Neural Network
    Feng Zhu, Ruihao Gong, Fengwei Yu, Xianglong Liu*, Yanfei Wang, Zhelong Li, Xiuqi Yang, Junjie Yan
    IEEE CVPR, 2020
    Forward and Backward Information Retention for Accurate Binary Neural Networks
    Haotong Qin, Ruihao Gong, Xianglong Liu*, Mingzhu Shen, Ziran Wei, Fengwei Yu, Jingkuan Song
    IEEE CVPR, 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*
    IJCAI, 2020
    Transductive Relation-Propagation Network for Few-shot Learning
    Yuqing Ma, Shihao Bai, Shan An, Wei Liu, Aishan Liu, Xiantong Zhen, Xianglong Liu*
    IJCAI, 2020
    Differentiable Soft Quantization: Bridging Full-Precision and Low-Bit Neural Networks
    Ruihao Gong, Xianglong Liu*, Shenghu Jiang, Tianxiang Li, Peng Hu, Jiazhen Lin, Fengwei Yu, Junjie Yan
    IEEE ICCV, 2019
    Perceptual-Sensitive GAN for Generating Adversarial Patches
    Aishan Liu, Xianglong Liu*, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie, Dacheng Tao
    AAAI, 2019
    Progressive Generative Hashing for Image Retrieval
    Yuqing Ma, Yue He, Fan Ding, Sheng Hu, Jun Li, Xianglong Liu*
    IJCAI, 2018
    Complementary Binary Quantization for Joint Multiple Indexing
    Qiang Fu, Xu Han, Xianglong Liu*, Jingkuan Song, Cheng Deng
    IJCAI, 2018
    Centered Weight Normalization in Accelerating Training of Deep Neural Networks
    Lei Huang, Xianglong Liu*, Yang Liu, Bo Lang, Dacheng Tao
    IEEE ICCV, 2017
    Boosting Complementary Hash Tables for Fast Nearest Neighbor Search
    Xianglong Liu, Cheng Deng, Yadong Mu, Zhujin Li
    AAAI, 2017
    Multilinear Hyperplane Hashing
    Xianglong Liu, Xinjie Fan, Cheng Deng, Zhujin Li, Hao Su, Dacheng Tao
    IEEE CVPR (Young Researcher Support), 2016
    Multi-View Complementary Hash Tables for Nearest Neighbor Search
    Xianglong Liu, Lei Huang, Cheng Deng, Jiwen Lu, Bo Lang
    IEEE ICCV, 2015
    Collaborative Hashing
    Xianglong Liu, Junfeng He, Cheng Deng, Bo Lang
    IEEE CVPR (Young Researcher Support), 2014
    Hash Bit Selection: a Unified Solution for Selection Problems in Hashing
    Xianglong Liu, Junfeng He, Bo Lang, Shih-Fu Chang
    IEEE CVPR, 2013.
    Journal: Hash Bit Selection for Nearest Neighbor Search. IEEE TIP, 2017. bibtex