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2024

• Accurate LoRA-Finetuning Quantization of LLMs via Information Retention. Haotong Qin, Xudong Ma, Xingyu Zheng, Xiaoyang Li, Yang Zhang, Shouda Liu, Jie Luo, Xianglong Liu*, Michele Magno. ICML, 2024.

• Flexible Residual Binarization for Image Super-Resolution. Yulun Zhang, Haotong Qin, Zixiang Zhao, Xianglong Liu*, Martin Danelljan, Fisher Yu. ICML, 2024.

• Compressing Large Language Models by Joint Sparsification and Quantization. Jinyang Guo, Jianyu Wu, Zining Wang, Jiaheng Liu, Ge Yang, Yifu Ding, Ruihao Gong, Haotong Qin, Xianglong Liu*. ICML, 2024.

• BiLLM: Pushing the Limit of Post-Training Quantization for LLMs. Wei Huang, Yangdong Liu, Haotong Qin, Ying Li, Shiming Zhang, Xianglong Liu, Michele Magno, Xiaojuan Qi. ICML, 2024.

• DB-LLM: Accurate Dual-Binarization for Efficient LLMs. Hong Chen, Chengtao Lv, Liang Ding, Haotong Qin, Xiabin Zhou, Yifu Ding, Xuebo Liu, Min Zhang, Jinyang Guo, Xianglong Liu*, Dacheng Tao. ACL Finding, 2024.

• TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models. Yushi Huang, Ruihao Gong, Jing Liu, Tianlong Chen, Xianglong Liu*. IEEE CVPR, 2024.

• Reg-PTQ: Regression-specialized Post-training Quantization for Fully Quantized Object Detector. Yifu Ding, Weilun Feng, Chuyan Chen, Jinyang Guo, Xianglong Liu*. IEEE CVPR, 2024.

• Scene-adaptive and Region-aware Multi-modal Prompt for Open Vocabulary Object Detection. Xiaowei Zhao, Duorui Wang, Zhide Liu, Yajun Gao, Xianglong Liu*. IEEE CVPR, 2024.

• NAPGuard: Towards Detecting Naturalistic Adversarial Patches. Siyang Wu, Jiakai Wang, Jiejie Zhao, Yazhe Wang, Xianglong Liu. IEEE CVPR, 2024.

• PTQ4SAM: Post-Training Quantization for Segment Anything. Chengtao Lv, Hong Chen, Jinyang Guo, Yifu Ding, Xianglong Liu. IEEE CVPR, 2024.

• LTA-PCS: Learnable Task-Agnostic Point Cloud Sampling. Jiaheng Liu, Jianhao Li, Kaisiyuan Wang, Hongcheng Guo, Jian Yang, Junran Peng, Ke Xu, Xianglong Liu, Jinyang Guo. IEEE CVPR, 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*. ICLR, 2024.

• Selective Focus: Efficient Post-training Quantization for Lane Detection. Yunqian Fan, Xiuying Wei, Ruihao Gong, Yuqing Ma, Xiangguo Zhang, Qi Zhang, Xianglong Liu*. AAAI, 2024.

• Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes. Ruihao Gong, Yang Yong, Zining Wang, Jinyang Guo, Xiuying Wei, Yuqing Ma, Xianglong Liu*. AAAI, 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. IEEE S&P, 2024.

• Generate Transferable Adversarial Physical Camouflages via Triplet Attention Suppression. Jiakai Wang, Xianglong Liu*, Zixin Yin, Yuxuan Wang, Jun Guo, Haotong Qin, Qing tao Wu, Aishan Liu. IJCV, 2024.

• Improving Deepfake Detection Generalization by Invariant Risk Minization. Zixin Yin, Jiakai Wang, Yisong Xiao, Hanqing Zhao, Tianlin Li, Wenbo Zhou, Aishan Liu, and Xianglong Liu. IEEE Transaction on Multimedia, 2024.

• 针对音频识别智能模型的物理世界音素对抗攻击. 王嘉凯，孔宇升，陈镇东，尹子鑫，胡琎，马宇晴，刘祥龙*. 计算机研究与发展 (Journal of Computer Research and Development), 2024.

2023

• QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution. Haotong Qin, Yulun Zhang, Yifu Ding, Yifan liu, Xianglong Liu*, Martin Danelljan, Fisher Yu. NeurIPS, 2023.

• BiMatting: Efficient Video Matting via Binarization. Haotong Qin, Lei Ke, Xudong Ma, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Xianglong Liu*, Fisher Yu. NeurIPS, 2023.

• BiBench: Benchmarking and Analyzing Network Binarization. Haotong Qin, Mingyuan Zhang, Yifu Ding, Aoyu Li, Zhongang Cai, Ziwei Liu, Fisher Yu, Xianglong Liu*. ICML, 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. USENIX Security Symposium, 2023.

• Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing. Yisong Xiao, Aishan Liu, Tianlin Li, Xianglong Liu. ACM ISSTA, 2023.

• Adaptive Contrastive Knowledge Distillation for BERT Compression. Jinyang Guo, Jiaheng Liu, Zining Wang, Yuqing Ma, Ruihao Gong, Ke Xu and Xianglong Liu*. Findings of ACL 2023.

• Annealing-based Label-Transfer Learning for Open World Object Detection. Yuqing Ma, Hainan Li, Zhange Zhang, Jinyang Guo，Ruihao Gong, Shanghang Zhang, Xianglong Liu*. IEEE CVPR, 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. IEEE CVPR, 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*. IEEE CVPR, 2023.

• Improving Robust Fairness via Balance Adversarial Training. Chunyu Sun, Chenye Xu, Chengyuan Yao, Siyuan Liang, Yichao Wu, Ding Liang, XiangLong Liu, Aishan Liu. AAAI, 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. MLSys, 2023.

• Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks. Jun Guo, Aishan Liu, Xingyu Zheng, Siyuan Liang, Yisong Xiao, Yichao Wu, Xianglong Liu. ACM MM, 2023.

• Outlier Suppression+: Accurate quantization of large language models by equivalent and effective shifting and scaling. Xiuying Wei, Yunchen Zhang, Yuhang Li, Xiangguo Zhang, Ruihao Gong, Jinyang Guo, Xianglong Liu. EMNLP, 2023.

• Towards Defending Multiple Lp-norm Bounded Adversarial Perturbations via Gated Batch Normalization. Aishan Liu, Shiyu Tang, Xinyun Chen, Lei Huang, Haotong Qin, Xianglong Liu*, Dacheng Tao. International Journal of Computer Vision, 2023.

• Diverse Sample Generation: Pushing the Limit of Generative Data-free Quantization. Haotong Qin, Yifu Ding, Xiangguo Zhang, Jiakai Wang, Xianglong Liu*, Jiwen Lu. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

• Revisiting Open World Object Detection. Xiaowei Zhao, Yuqing Ma, Duorui Wang, Yifan Shen, Yixuan Qiao, Xianglong Liu*. IEEE Transactions on Circuits and Systems for Video Technology, 2023.

• BiFSMNv2: Pushing Binary Neural Networks for Keyword Spotting to Real-Network Performance. Haotong Qin, Xudong Ma, Yifu Ding, Xiaoyang Li, Yang Zhang, Zejun Ma, Jiakai Wang, Jie Luo, Xianglong Liu*. IEEE Transactions on Neural Networks and Learning Systems, 2023.

• Temporal Speciation Network for Few-Shot Object Detection. Xiaowei Zhao, Xianglong Liu, Yuqing Ma, Shihao Bai, Yifan Shen, Zeyu Hao, Aishan Liu. IEEE Transactions on Multimedia, 2023.

• Spatio-Temporal Adaptive Network with Bidirectional Temporal Difference for Action Recognition. Zhilei Li, Jun Li, Yuqing Ma, Rui Wang, Zhiping Shi, Yifu Ding, Xianglong Liu. IEEE Transactions on Circuits and Systems for Video Technology, 2023.

• A Meaningful Learning Method for Zero-shot Semantic Segmentation. Xianglong Liu, Shihao Bai, Shan An, Shuo Wang, Wei Liu, Xiaowei Zhao, Yuqing Ma. SCIENCE CHINA Information Sciences, 2023.

• SeeMore: a Spatio-temporal Predictive Model with Bidirectional Distillation and Level-specific Meta Adaptation. Yuqing Ma, Wei Liu, Yajun Gao, Yang Yuan, Shihao Bai, Haotong Qin, Xianglong Liu*. SCIENCE CHINA Information Sciences, 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 Recognition, 2023.

• 面向深度强化学习的对抗攻防综述. Aishan Liu, Jun Guo, Simin Li, Yisong Xiao, Xianglong Liu*, Dacheng Tao. 计算机学报 (Chinese Journal of Computers), 2023.

• 智能系统全生命周期安全测试理论与方法. 王嘉凯，刘艾杉，李思民，刘祥龙*，吴文峻. 智能安全 (Artificial Intelligence Security), 2023. [创刊十大优秀论文]

• 基于稳定信息的小数据学习方法. 马宇晴，张湛舸，刘卫，刘祥龙*. 智能安全 (Artificial Intelligence Security), 2023. [创刊十大优秀论文]

2022

• 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.

• Harnessing Perceptual Adversarial Patches for Crowd Counting. Shunchang Liu, Jiakai Wang, Aishan Liu, Yingwei Li, Yijie Gao, Xianglong Liu, Dacheng Tao. ACM CCS, 2022.

• Generating Transferable Adversarial Examples against Vision Transformers. Yuxuan Wang, Jiakai Wang, Zixin Yin, Ruihao Gong, Jingyi Wang, Aishan Liu, Xianglong Liu. ACM MM, 2022.

• Towards Accurate Post-Training Quantizationfor Vision Transformer. Yifu Ding, Haotong Qin, Qinghua Yan, Zhenhua Chai, Junjie Liu, Xiaolin Wei, Xianglong Liu*. ACM MM, 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*. ACM MM, 2022.

• Frequency Domain Model Augmentation for Adversarial Attack. Yuyang Long, Qilong Zhang, Boheng Zeng, Lianli Gao, Xianglong Liu, Jian Zhang, Jingkuan Song. ECCV, 2022.

• Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies. Xingrun Xing, Yangguang Li, Wei Li, Wenrui Ding, Yalong Jiang, Yufeng Wang, Jing Shao, Chunlei Liu, Xianglong Liu. ECCV, 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.

• QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization. Xiuying Wei, Ruihao Gong, Yuhang Li, Xianglong Liu*, Fengwei Yu. ICLR, 2022. [PDF][code]

• BiBERT: Accurate Fully Binarized BERT. Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu*. ICLR, 2022. [PDF][code]

• 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. [PDF][code]

• 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. [PDF][code]

• Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack. Ye Liu, Yaya Cheng, Lianli Gao, Xianglong Liu, Qilong Zhang, Jingkuan Song. IEEE CVPR, 2022. [PDF][code]

• Delving Deep into the Generalization of Vision Transformers under Distribution Shifts. Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang, Daisheng Jin, Qiang Zhou, Zhongang Cai, Haiyu Zhao, Xianglong Liu, Ziwei Liu. IEEE CVPR, 2022. [PDF][code]

• Delving into the Estimation Shift of Batch Normalization in a Network. Lei Huang, Yi Zhou, Tian Wang, Jie Luo, Xianglong Liu. IEEE CVPR, 2022. [PDF][code]

• Distribution-sensitive Information Retention for Accurate Binary Neural Network. Haotong Qin, Xiangguo Zhang, Ruihao Gong, Yifu Ding, Yi Xu, Xianglong Liu*. International Journal of Computer Vision, 2022.[PDF][code]

• Region-wise Generative Adversarial Image Inpainting for Large Missing Areas. Yuqing Ma, Xianglong Liu*, Shihao Bai, Lei Wang, Aishan Liu, Dacheng Tao, Edwin R. Hancock. IEEE Transactions on Cybernetics, 2022.[PDF][code]

2021

• 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. [data and code]

• Towards Real-World Prohibited Item Detection: A Large-Scale X-Ray Benchmark. Boying Wang, Libo Zhang, Longyin Wen, Xianglong Liu, Yanjun Wu. 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[PDF][data and code]

• 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. [PDF][data and code]

• 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. [PDF][data and code]

• Stratified Rule-Aware Network for Abstract Visual Reasoning. Sheng Hu, Yuqing Ma, Xianglong Liu*, Yanlu Wei, Shihao Bai. AAAI, 2021. [data and code]

• Hierarchical Generative Adversarial Networks for Single Image Super-Resolution. Weimin Chen, Yuqing Ma, Xianglong Liu*, Yi Yuan. WACV, 2021.

• Understanding adversarial robustness via critical attacking route. Tianlin Li, Aishan Liu, Xianglong Liu*, Yitao Xu, Chongzhi Zhang, Xiaofei Xie. Information Sciences, 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 Transactions on Image Processing, 2021.

• Training Robust Deep Neural Networks via Adversarial Noise Propagation. Aishan Liu, Xianglong Liu*, Hang Yu, Chongzhi Zhang, Qiang Liu, Dacheng Tao. IEEE Transactions on Image Processing, 2021.

• Universal Adversarial Patch Attack for Automatic Checkout using Perceptual and Attentional Bias. Jiakai Wang, Aishan Liu, Xiao Bai, Xianglong Liu*. IEEE Transactions on Image Processing, 2021.

• Two-branch Attention Network via Efficient Semantic Coupling for One-shot Learning. Jun Li, Duorui Wang, Xianglong Liu*, Zhiping Shi, Meng Wang. IEEE Transactions on Image Processing, 2021.

• Transductive Relation-Propagation with Decoupling Training for Few-Shot Learning. Yuqing Ma, Shihao Bai, Wei Liu, Shuo Wang, Yue Yu, Xiao Bai, Xianglong Liu*, Meng Wang. IEEE Transactions on Neural Networks and Learning Systems, 2021.

• Self-Supervised Multiscale Adversarial Regression Network for Stereo Disparity Estimation. Chen Wang, Xiao Bai, Xiang Wang, Xianglong Liu, Jun Zhou, Xinyu Wu, Hongdong Li, Dacheng Tao. IEEE Transactions on Cybernetics, 2021.

2020

• Occluded Prohibited Items Detection: An X-ray Security Inspection Benchmark and De-occlusion Attention Module. Yanlu Wei, Renshuai Tao, Zhangjie Wu, Yuqing Ma, Libo Zhang, Xianglong Liu*. ACM MM, 2020. [data and code]

• Spatiotemporal Attacks for Embodied Agents. Aishan Liu, Tairan Huang, Xianglong Liu*, Yitao Xu, Yuqing Ma, Xinyun Chen, Stephen Maybank, Dacheng Tao. ECCV, 2020. [code][media]

• Bias-based Universal Adversarial Patch Attack for Automatic Check-out. Aishan Liu, Jiakai Wang, Xianglong Liu*, Chongzhi Zhang, Bowen Cao, Hang Yu. ECCV, 2020. [code][media]

• Patch-wise Attack for Fooling Deep Neural Network. Lianli Gao, Qilong Zhang, Jingkuan Song, Xianglong Liu, Hengtao Shen. ECCV, 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.

• 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.

• Forward and Backward Information Retention for Accurate Binary Neural Networks. Haotong Qin, Ruihao Gong, Xianglong Liu*, Mingzhu Shen, Ziran Wei, Fengwei Yu, Jingkuan Song. CVPR, 2020. [code]

• Towards Unified INT8 Training for Convolutional Neural Network. Feng Zhu, Ruihao Gong, Fengwei Yu, Xianglong Liu*, Yanfei Wang, Zhelong Li, Xiuqi Yang, Junjie Yan. CVPR, 2020. [media]

• Rotation Consistent Margin Loss for Efficient Low-bit Face Recognition. Yudong Wu, Yichao Wu, Ruihao Gong, Yuanhao Lv, Ken Chen, Ding Liang, Xiaolin Hu, Xianglong Liu, Junjie Yan. CVPR, 2020.

• Learning Unseen Concepts via Hierarchical Decomposition and Composition. Muli Yang, Cheng Deng, Junchi Yan, Xianglong Liu, Dacheng Tao. CVPR, 2020.

• Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization. Ruyi Ji, Longyin Wen, Libo Zhang, Dawei Du, Yanjun Wu, Chen Zhao, Xianglong Liu, Feiyue Huang. CVPR, 2020.

• Graph Attention Based Proposal 3D ConvNets for Action Detection. Jun Li, Xianglong Liu*, Zhuofan Zong, Wanru Zhao, Mingyuan Zhang, Jingkuan Song. AAAI, 2020.

• Stein Variational Inference for Discrete Distributions. Jun Han, Fan Ding, Xianglong Liu, Lorenzo Torresani, Jian Peng, Qiang Liu. AISTAT, 2020.

• DMS: Differentiable Dimension Search for Binary Neural Networks. Yuhang Li, Ruihao Gong, Fengwei Yu, Xin Dong, Xianglong Liu. ICLR NAS workshop, 2020.

• Balanced Binary Neural Networks with Gated Residual. Mingzhu Shen, Xianglong Liu*, Ruihao Gong, Kai Han. ICASSP, 2020.

• Distributed Complementary Binary Quantization for Joint Hash Table Learning. Xianglong Liu, Qiang Fu, Deqing Wang, Xiao Bai, Xinyu Wu, Dacheng Tao. IEEE Transactions on Neural Networks and Learning Systems, 2020.

• Spatio-Temporal Attention Networks for Action Recognition and Detection. Jun Li, Xianglong Liu*, Mingyuan Zhang, Wenxuan Zhang, Jingkuan Song, Sebe Nicu. IEEE Transactions on Multimedia, 2020.

• Fast Nearest Subspace Search via Random Angular Hashing. Yi Xu, Xianglong Liu*, Binshuai Wang, Renshuai Tao, Ke Xia, Xinbin Cao. IEEE Transactions on Multimedia, 2020.

• Boosting Temporal Binary Coding for Large-scale Video Search. Yan Wu, Xianglong Liu*, Haotong Qin, Ke Xia, Sheng Hu, Yuqing Ma, Meng Wang. IEEE Transactions on Multimedia, 2020.

• Multi-Task Consistency-Preserving Adversarial Hashing for Cross-Modal Retrieval. De Xie, Cheng Deng*, Chao Li, Xianglong Liu*, Dacheng Tao. IEEE Transactions on Image Processing, 2020.

• Binary Neural Network: A Survey. Haotong Qin, Ruihao Gong, Xianglong Liu*, Xiao Bai, Jingkuan Song, Nicu Sebe. Pattern Recognition, 2020. [media]

• Projection Based Weight Normalization: Efficient Method for Optimization on Oblique Manifold in Deep Neural Networks. Lei Huang, Xianglong Liu*,Jie Qin, Fan Zhu, Li Liu, Ling Shao. Pattern Recognition, 2020.

• Spatio-Temporal Deformable 3D ConvNets with Attention for Action Recognition. J Li, X Liu*, M Zhang, D Wang. Pattern Recognition, 2020.

• Learning Binary Code for Fast Nearest Subspace Search. L Zhou, X Bai, X Liu, J Zhou, ER Hancock. Pattern Recognition, 2020.

2019

• 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. ICCV, 2019.

• Adversarial Fine-Grained Composition Learning for Unseen Attribute-Object Recognition. K. Wei, M. Yang, H. Wang, C. Deng*, X. Liu*. ICCV, 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. IJCAI, 2019.

• Latent Distribution Preserving Deep Subspace Clustering. Lei Zhou, Xiao Bai, Dong Wang, Xianglong Liu*, Jun Zhou, Edwin Hancock. IJCAI, 2019.

• Graph Convolutional Network Hashing for Cross-Modal Retrieval. Ruiqing Xu, Chao Li, Junchi Yan, Cheng Deng, Xianglong Liu. IJCAI, 2019.

• Perceptual-Sensitive GAN for Generating Adversarial Patches. Aishan Liu, Xianglong Liu*, Jiaxin Fan, Yuqing Ma, Anlan Zhang, Huiyuan Xie, Dacheng Tao. AAAI, 2019.

• Coupled CycleGAN: Unsupervised Hashing Network for Cross-Modal Retrieval. Chao Li, Cheng Deng, Lei Wang, De Xie, Xianglong Liu. AAAI, 2019.

• Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering. Xiangpeng Li, Jingkuan Song, Lianli Gao, Xianglong Liu, Wenbing Huang, Xiangnan He, Chuang Gan. AAAI, 2019.

• Deliberate Attention Networks for Image Captioning. Lianli Gao, Kaixuan Fan, Jingkuan Song, Xianglong Liu, Xing Xu, Heng Tao Shen. AAAI, 2019.

• Quarter-point Codeword Expansion for Product Quantization. Shan An, Zhibiao Huang, Guangfu Che, Xianglong Liu, Xin Ma, Yu Chen . ICME, 2019.

• Fast and Incremental Loop closure Detection using Proximity Graphs. Shan An, Guangfu Che, Fangru Zhou, Xianglong Liu, Xin Ma, Yu Chen. IROS, 2019. [code]

• A general non-parametric active learning framework for classification on multiple manifolds. L Huang, Y Ma, X Liu*. Pattern Recognition Letters, 2019.

• Active Transfer Learning Network: A Unified Deep Joint Feature Learning Model For Hyperspectral Image Classification. Cheng Deng, Yumeng Xue, Xianglong Liu, Chao Li, Dacheng Tao. IEEE Transactions on Geoscience and Remote Sensing, 2019.

2018

• Random Angular Projection for Fast Nearest Subspace Search. Binshuai Wang, Xianglong Liu*, Ke Xia, Kotagiri Ramamohanarao, Dacheng Tao. PCM (Best Student Paper), 2018.

• Examine before You Answer: Multi-task Learning with Adaptive-attentions for Multiple-choice VQA. Jingkuan Song, Pengpeng Zeng, Lianli Gao, Xianglong Liu, Heng Tao Shen. ACM MM, 2018.

• 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.

• Deep Joint Semantic-Embedding Hashing. Ning Li, Chao Li, Cheng Deng, Xianglong Liu, Xinbo Gao. IJCAI, 2018.

• Dual Conditional GANs for Face Aging and Rejuvenation. Jingkuan Song, Jingqiu Zhang, Lianli Gao, Xianglong Liu, Heng Tao Shen. IJCAI, 2018.

• Binary Coding by Matrix Classifier for Efficient Subspace Retrieval. Lei Zhou, Xiao Bai, Xianglong Liu, Jun Zhou. ACM ICMR, 2018.

• Orthogonal Weight Normalization: Solution to Optimization over Multiple Dependent Stiefel Manifolds in Deep Neural Networks. Lei Huang, Xianglong Liu, Bo Lang, Admas Wei Yu, Bo Li. AAAI, 2018.

• New L21-Norm Relaxation of Multi-Way Graph Cut for Clustering. Xu Yang, Cheng Deng, Xianglong Liu*, Feiping Nie. AAAI, 2018.

• Dictionary Learning in Optimal Metric Space. Jiexi Yan, Cheng Deng, Xianglong Liu. AAAI, 2018.

• Direct Shape Regression Networks for End-to-End Face Alignment. Xin Miao, Xiantong Zhen, Xianglong Liu, Vassilis Athitsos, Heng Huang. IEEE CVPR, 2018.

• Active Multi-Kernel Domain Adaptation for Hyperspectral Image Classification. Cheng Deng, Xianglong Liu*, Chao Li, Dacheng Tao. Pattern Recognition, 2018.

• Triplet-Based Deep Hashing Network for Cross-Modal Retrieval. Cheng Deng, Zhaojia Chen, Xianglong Liu, Xinbo Gao, Dacheng Tao. IEEE Transactions on Image Processing, 2018.

• Two-Stream 3-D convNet Fusion for Action Recognition in Videos With Arbitrary Size and Length. Xuanhan Wang, Lianli Gao, Peng Wang, Xiaoshuai Sun, Xianglong Liu. IEEE Transactions on Multimedia, 2018.

2017

• Orthogonal Weight Normalization: Solution to Optimization over Multiple Dependent Stiefel Manifolds in Deep Neural Networks. Lei Huang, Xianglong Liu, Bo Lang, Admas Wei Yu, Bo Li. preprint (arXiv:1709.06079).

• Centered Weight Normalization in Accelerating Training of Deep Neural Networks. Lei Huang, Xianglong Liu*, Yang Liu, Bo Lang, Dacheng Tao. IEEE ICCV, 2017.

• Temporal Binary Coding for Large-Scale Video Search. Ke Xia, Yuqing Ma, Xianglong Liu*, Yadong Mu, Li Liu. ACM MM, 2017.

• Boosting Complementary Hash Tables for Fast Nearest Neighbor Search. Xianglong Liu, Cheng Deng, Yadong Mu, Zhujin Li. AAAI, 2017. [PDF]

• Pairwise Relationship Guided Deep Hashing for Cross-Modal Retrieval. Erkun Yang, Cheng Deng, Wei Liu, Xianglong Liu, Dacheng Tao, Xinbao Gao. AAAI, 2017.

• Deep Sketch Hashing: Fast Free-hand Sketch-Based Image Retrieval. Li Liu, Fumin Shen, Yuming Shen, Xianglong Liu, Ling Shao. IEEE CVPR, 2017. [PDF][Code]

• Multi-Class Support Vector Machine via Maximizing Multi-Class Margins. Jie Xu, Xianglong Liu, Zhouyuan Huo, Cheng Deng, Feiping Nie, Heng Huang. IJCAI, 2017.

• Hash Bit Selection for Nearest Neighbor Search. Xianglong Liu, Junfeng He, Shih-Fu Chang. IEEE Transactions on Image Processing, 2017.

• Distributed Adaptive Binary Quantization for Fast Nearest Neighbor Search. Xianglong Liu, Zhujin Li, Cheng Deng, Dacheng Tao. IEEE Transactions on Image Processing, 2017.

2016

• Multilinear Hyperplane Hashing. Xianglong Liu, Xinjie Fan, Cheng Deng, Zhujin Li, Hao Su, Dacheng Tao. IEEE CVPR, 2016. [PDF]

• Adaptive Binary Quantization for Fast Nearest Neighbor Search. Zhujin Li, Xianglong Liu*, Junjie Wu, Hao Su. ECAI, 2016. [PDF][Slides][Code]

• Efficient Segmentation for Region-based Image Retrieval Using Edge Integrated Minimum Spanning Tree. Yang Liu, Lei Huang, Siqi Wang, Xianglong Liu, Bo Lang. ICPR, 2016.

• Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search. Xianglong Liu, Lei Huang, Cheng Deng, Bo Lang, Dacheng Tao. IEEE Transactions on Image Processing, 2016.

• Query-Adaptive Reciprocal Hash Tables for Nearest Neighbor Search. Xianglong Liu, Cheng Deng, Bo Lang, Dacheng Tao, Xuelong Li. IEEE Transactions on Image Processing, 2016.

• Structure Sensitive Hashing with Adaptive Product Quantization. Xianglong Liu, Bowen Du, Cheng Deng, Ming Liu, Bo Lang. IEEE Transactions on Cybernetics, 2016.

• Bit Selection via Walks on Graph for Hash-based Nearest Neighbor Search. Ya Wang, Xianglong Liu, Danchen Zhang, Deqing Wang, Yuan Yang. Neurocomputing, 2016.

• A Novel Rotation Adaptive Object Detection Method Based on Pair Hough Model. Yang Liu, Lei Huang, Xianglong Liu, Bo Lang. Neurocomputing, 2016.

• Unsupervised Feature Selection through Gram-Schmidt Orthogonalization - A Word Co-occurrence Perspective. Deqing Wang, Hui Zhang, Rui Liu, Xianglong Liu, Jing Wang. Neurocomputing, 2016.

• Face Identification with Second-order Pooling in Single-layer Networks. Fumin Shen, Yang Yang, Xiang Zhou, Xianglong Liu, Jie Shao. Neurocomputing, 2016.

2015

• Multi-View Complementary Hash Tables for Nearest Neighbor Search. Xianglong Liu, Lei Huang, Cheng Deng, Jiwen Lu, Bo Lang. IEEE ICCV, 2015. [PDF][Poster][Spotlights]

• Fast Graph Similarity Search via Locality Sensitive Hashing. Boyu Zhang, Xianglong Liu*, Bo Lang. PCM, 2015.

• Adaptive Multi-Bit Quantization for Hashing. Cheng Deng, Huiru Deng, Xianglong Liu*, Yuan Yuan. Neurocomputing. 2015. [Code]

• Large-Scale Multi-Task Image Labeling with Adaptive Relevance Discovery and Feature Hashing. Cheng Deng, Xianglong Liu, Yadong Mu, Jie Li. Signal Processing, 2015.

• Online Semi-Supervised Annotation via Proxy-based Local Consistency Propagation. Lei Huang, Xianglong Liu, Binqiang Ma, Bo Lang. Neurocomputing, 2015.

• Large-Scale Unsupervised Hashing with Shared Structure Learning. Xianglong Liu, Yadong Mu, Danchen Zhang, Bo Lang, Xuelong Li. IEEE Transactions on Cybernetics, 2015.[Code]

2014

• Collaborative Hashing. Xianglong Liu, Junfeng He, Cheng Deng, Bo Lang. IEEE CVPR (young researcher support), 2014.[PDF][Spotlights][Poster][Code]

• Query-Adaptive Hash Code Ranking for Fast Nearest Neighbor Search. Tianxu Ji, Xianglong Liu*, Cheng Deng, Lei Huang, Bo Lang. ACM MM (short paper), 2014. [PDF][Code]

• Graph-based Active Semi-supervised Learning: a New Perspective for Relieving Multi-class Annotation Labor. Lei Huang, Yang Liu, Xianglong Liu, Xindong Wang, Bo Lang. IEEE ICME, 2014.

• Image Super-resolution Based on Sparse Representation with Joint Constraints. Jie Xu, Cheng Deng, Xianglong Liu, Jie Li. ACM ICIMCS, 2014.

• Mixed Image-Keyword Query Adaptive Hashing over Multi-Label Images. Xianglong Liu, Yadong Mu, Bo Lang, Shih-Fu Chang. ACM Transactions on Multimedia Computing Communications and Applications, 10(2): 22:1-22:21, 2014. [PDF]

• Multiple Feature Kernel Hashing for Large-Scale Visual Search. Xianglong Liu, Junfeng He, Bo Lang. Pattern Recognition, 47(2): 748-757, 2014.

2013

• Reciprocal Hash Tables for Nearest Neighbor Search. Xianglong Liu, Junfeng He, Bo Lang. AAAI, 2013. [PDF][Slides][Poster]

• Hash Bit Selection: a Unified Solution for Selection Problems in Hashing. Xianglong Liu, Junfeng He, Bo Lang, Shih-Fu Chang. IEEE CVPR, 2013. [PDF][Supplementary][Slides (in chinese)][Poster][Code][Data]

• Efficient Semi-supervised Annotation with Proxy-based Local Consistency Propagation. Lei Huang, Yang Wang, Xianglong Liu, Bo Lang. IEEE ICME, 2013.

• Robust Clustering for Social Annotated Images. Yang Wang, Jian Zheng, Xianglong Liu, Bo Lang. ACM ICIMCS, 2013.

Before 2013

• Compact Kernel Hashing with Multiple Features. Xianglong Liu, Junfeng He, Di Liu, Bo Lang. ACM MM (short paper), 2012. [PDF][Supplementary][Poster][Code][Data]

• Compact Hashing for Mixed Image-Keyword Query over Multi-Label Images. Xianglong Liu, Yadong Mu, Bo Lang, Shih-Fu Chang. ACM ICMR (oral, 13.8%), 2012. [PDF][Slides][Code][Data]

• Mobile Product Search with Bag of Hash Bits and Boundary Reranking. Junfeng He, Jinyuan Feng, Xianglong Liu, Tao Cheng, Tai-Hsu Lin, Hyunjin Chung, Shih-Fu Chang. IEEE CVPR, 2012. [PDF][Demo video]

• Multimedia Semantics-Aware Query-Adaptive Hashing with Bits Reconfigurability. Yadong Mu, Xiangyu Chen, Xianglong Liu, Tat-Seng Chua, Shuicheng Yan. International Journal of Multimedia Information Retrieval, 2012. [PDF]

• Feature Grouping and Local Soft Match for Mobile Visual Search. Xianglong Liu, Bo Lang, Yi Xu, Bo Cheng. Pattern Recognition Letters, 33(3): 239-246, 2012.

• Search by Mobile Image Based on Visual and Spatial Consistency. Xianglong Liu, Yihua Lou, Wei Yu, Bo Lang. IEEE ICME (Best Paper Candidate, oral, 8%), 2011. [Project][Mobile Visual Search Dataset]

• An Improved Noise-Robust Voice Activity Detector Based on Hidden Semi-Markov Models. Xianglong Liu*,Yuan Liang*, Yihua Lou, Baosong Shan.
  Pattern Recognition Letters (* indicates equal contribution), 32(7): 1044-1053

• Noise-Robust Voice Activity Detector Based on Hidden Semi-Markov Models. Xianglong Liu,Yuan Liang, Yihua Lou, He Li, Baosong Shan. IAPR ICPR (oral, 18%), pp 81-84, 2010.

• A Heuristic Algorithm for Cube Packing with Time Schedule. Li Wei, Huang Wenqi, Jiang Dongchen, Liu Xianglong. Science in China (F) 2010 Vol. 53 (1): 18-29, 2010. [Project]