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ORCIDXianglong Liu 0001
Person information
- affiliation: Beihang University, State Key Laboratory of Software Development Environment, Beijing, China
Other persons with the same name
- Xianglong Liu
- Xianglong Liu 0002 — Zhengzhou University of Light Industry, School of Electrical and Information Engineering, Zhengzhou, China
- Xianglong Liu 0003 — Wuhan University, Transportation Research Center, Wuhan, China (and 1 more)
- Xianglong Liu 0004
![[0000-0002-4907-5279]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-4907-5279")
— Harbin Institute of Technology, Harbin, China - Xianglong Liu 0005 — Chinese Academy of Sciences, Institute of Software, Beijing, China
- Xianglong Liu 0006 — China Academy of Transportation Sciences, Beijing, China
- Xianglong Liu 0007 — Institute of Automation, Chinese Academy of Sciences, China
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2020 – today
- 2024
[j65]Aishan Liu, Shiyu Tang, Xinyun Chen, Lei Huang, Haotong Qin, Xianglong Liu, Dacheng Tao:
Towards Defending Multiple ℓ p-Norm Bounded Adversarial Perturbations via Gated Batch Normalization. Int. J. Comput. Vis. 132(6): 1881-1898 (2024)- [j64]Xiaowei Zhao, Yuqing Ma, Duorui Wang, Yifan Shen, Yixuan Qiao, Xianglong Liu:
Revisiting Open World Object Detection. IEEE Trans. Circuits Syst. Video Technol. 34(5): 3496-3509 (2024) - [j63]Jiakai Wang, Ye Tao, Yichi Zhang, Wanting Liu, Yusheng Kong, Shaolin Tan, Rongen Yan, Xianglong Liu:
Adversarial Examples Against WiFi Fingerprint-Based Localization in the Physical World. IEEE Trans. Inf. Forensics Secur. 19: 8457-8471 (2024) - [j62]Simin Li, Huangxinxin Xu, Jiakai Wang, Ruixiao Xu, Aishan Liu, Fazhi He, Xianglong Liu, Dacheng Tao:
Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection. IEEE Trans. Image Process. 33: 2714-2729 (2024) - [j61]Zixin Yin, Jiakai Wang, Yisong Xiao, Hanqing Zhao, Tianlin Li, Wenbo Zhou, Aishan Liu, Xianglong Liu:
Improving Deepfake Detection Generalization by Invariant Risk Minimization. IEEE Trans. Multim. 26: 6785-6798 (2024) - [j60]Haotong Qin, Xudong Ma, Yifu Ding, Xiaoyang Li, Yang Zhang, Zejun Ma, Jiakai Wang, Jie Luo, Xianglong Liu:
BiFSMNv2: Pushing Binary Neural Networks for Keyword Spotting to Real-Network Performance. IEEE Trans. Neural Networks Learn. Syst. 35(8): 10674-10686 (2024) - [c122]Yunqian Fan, Xiuying Wei, Ruihao Gong, Yuqing Ma, Xiangguo Zhang, Qi Zhang, Xianglong Liu:
Selective Focus: Investigating Semantics Sensitivity in Post-training Quantization for Lane Detection. AAAI 2024: 11936-11943 - [c121]Ruihao Gong, Yang Yong, Zining Wang, Jinyang Guo, Xiuying Wei, Yuqing Ma, Xianglong Liu:
Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes. AAAI 2024: 12190-12198 - [c120]Hong Chen, Chengtao Lv, Liang Ding, Haotong Qin, Xiabin Zhou, Yifu Ding, Xuebo Liu, Min Zhang, Jinyang Guo, Xianglong Liu, Dacheng Tao:
DB-LLM: Accurate Dual-Binarization for Efficient LLMs. ACL (Findings) 2024: 8719-8730 - [c119]Chengtao Lv, Hong Chen, Jinyang Guo, Jinyang Guo, Jinyang Guo, Yifu Ding, Xianglong Liu:
PTQ4SAM: Post-Training Quantization for Segment Anything. CVPR 2024: 15941-15951 - [c118]Xiaowei Zhao, Xianglong Liu, Duorui Wang, Yajun Gao, Zhide Liu:
Scene-adaptive and Region-aware Multi-modal Prompt for Open Vocabulary Object Detection. CVPR 2024: 16741-16750 - [c117]Siyang Wu, Jiakai Wang, Jiejie Zhao, Yazhe Wang, Xianglong Liu:
NAPGuard: Towards Detecting Naturalistic Adversarial Patches. CVPR 2024: 24367-24376 - [c116]Simin Li, Jun Guo, Jingqiao Xiu, Ruixiao Xu, Xin Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu:
Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game. ICLR 2024 - [c115]Jinyang Guo, Jianyu Wu, Zining Wang, Jiaheng Liu, Ge Yang, Yifu Ding, Ruihao Gong, Haotong Qin, Xianglong Liu:
Compressing Large Language Models by Joint Sparsification and Quantization. ICML 2024 - [c114]Wei Huang, Yangdong Liu, Haotong Qin, Ying Li, Shiming Zhang, Xianglong Liu, Michele Magno, Xiaojuan Qi:
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs. ICML 2024 - [c113]Haotong Qin, Xudong Ma, Xingyu Zheng, Xiaoyang Li, Yang Zhang, Shouda Liu, Jie Luo, Xianglong Liu, Michele Magno:
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention. ICML 2024 - [c112]Yulun Zhang, Haotong Qin, Zixiang Zhao, Xianglong Liu, Martin Danelljan, Fisher Yu:
Flexible Residual Binarization for Image Super-Resolution. ICML 2024 - [c111]Haodi Wang, Kai Dong, Zhilei Zhu, Haotong Qin, Aishan Liu, Xiaolin Fang, Jiakai Wang, Xianglong Liu:
Transferable Multimodal Attack on Vision-Language Pre-training Models. SP 2024: 1722-1740 - [i93]Wei Huang, Yangdong Liu, Haotong Qin, Ying Li, Shiming Zhang, Xianglong Liu, Michele Magno, Xiaojuan Qi:
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs. CoRR abs/2402.04291 (2024) - [i92]Haotong Qin, Xudong Ma, Xingyu Zheng, Xiaoyang Li, Yang Zhang, Shouda Liu, Jie Luo, Xianglong Liu, Michele Magno:
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention. CoRR abs/2402.05445 (2024) - [i91]Hong Chen, Chengtao Lv, Liang Ding, Haotong Qin, Xiabin Zhou, Yifu Ding, Xuebo Liu, Min Zhang, Jinyang Guo, Xianglong Liu, Dacheng Tao:
DB-LLM: Accurate Dual-Binarization for Efficient LLMs. CoRR abs/2402.11960 (2024) - [i90]Leo Chen, Benjamin Boardley, Ping Hu, Yiru Wang, Yifan Pu, Xin Jin, Yongqiang Yao, Ruihao Gong, Bo Li, Gao Huang, Xianglong Liu, Zifu Wan, Xinwang Chen, Ning Liu, Ziyi Zhang, Dongping Liu, Ruijie Shan, Zhengping Che, Fachao Zhang, Xiaofeng Mou, Jian Tang, Maxim Chuprov, Ivan Malofeev, Alexander Goncharenko, Andrey Shcherbin, Arseny Yanchenko, Sergey Alyamkin, Xiao Hu, George K. Thiruvathukal, Yung-Hsiang Lu:
2023 Low-Power Computer Vision Challenge (LPCVC) Summary. CoRR abs/2403.07153 (2024) - [i89]Xingyu Zheng, Haotong Qin, Xudong Ma, Mingyuan Zhang, Haojie Hao, Jiakai Wang, Zixiang Zhao, Jinyang Guo, Xianglong Liu:
BinaryDM: Towards Accurate Binarization of Diffusion Model. CoRR abs/2404.05662 (2024) - [i88]Wei Huang, Xudong Ma, Haotong Qin, Xingyu Zheng, Chengtao Lv, Hong Chen, Jie Luo, Xiaojuan Qi, Xianglong Liu, Michele Magno:
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study. CoRR abs/2404.14047 (2024) - [i87]Chengtao Lv, Hong Chen, Jinyang Guo, Yifu Ding, Xianglong Liu:
PTQ4SAM: Post-Training Quantization for Segment Anything. CoRR abs/2405.03144 (2024) - [i86]Xinwei Zhang, Aishan Liu, Tianyuan Zhang, Siyuan Liang, Xianglong Liu:
Towards Robust Physical-world Backdoor Attacks on Lane Detection. CoRR abs/2405.05553 (2024) - [i85]Ruihao Gong, Yang Yong, Zining Wang, Jinyang Guo, Xiuying Wei, Yuqing Ma, Xianglong Liu:
Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes. CoRR abs/2405.05808 (2024) - [i84]Ruihao Gong, Yang Yong, Shiqiao Gu, Yushi Huang, Yunchen Zhang, Xianglong Liu, Dacheng Tao:
LLM-QBench: A Benchmark Towards the Best Practice for Post-training Quantization of Large Language Models. CoRR abs/2405.06001 (2024) - [i83]Yunqian Fan, Xiuying Wei, Ruihao Gong, Yuqing Ma, Xiangguo Zhang, Qi Zhang, Xianglong Liu:
Selective Focus: Investigating Semantics Sensitivity in Post-training Quantization for Lane Detection. CoRR abs/2405.06264 (2024) - [i82]Wei Huang, Haotong Qin, Yangdong Liu, Yawei Li, Xianglong Liu, Luca Benini, Michele Magno, Xiaojuan Qi:
SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models. CoRR abs/2405.14917 (2024) - [i81]Tianyuan Zhang, Lu Wang, Hainan Li, Yisong Xiao, Siyuan Liang, Aishan Liu, Xianglong Liu, Dacheng Tao:
LanEvil: Benchmarking the Robustness of Lane Detection to Environmental Illusions. CoRR abs/2406.00934 (2024) - [i80]Zonghao Ying, Aishan Liu, Tianyuan Zhang, Zhengmin Yu, Siyuan Liang, Xianglong Liu, Dacheng Tao:
Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt. CoRR abs/2406.04031 (2024) - [i79]Zonghao Ying, Aishan Liu, Xianglong Liu, Dacheng Tao:
Unveiling the Safety of GPT-4o: An Empirical Study using Jailbreak Attacks. CoRR abs/2406.06302 (2024) - [i78]Yisong Xiao, Aishan Liu, QianJia Cheng, Zhenfei Yin, Siyuan Liang, Jiapeng Li, Jing Shao, Xianglong Liu, Dacheng Tao:
GenderBias-VL: Benchmarking Gender Bias in Vision Language Models via Counterfactual Probing. CoRR abs/2407.00600 (2024) - [i77]Shilong Tian, Hong Chen, Chengtao Lv, Yu Liu, Jinyang Guo, Xianglong Liu, Shengxi Li, Hao Yang, Tao Xie:
QVD: Post-training Quantization for Video Diffusion Models. CoRR abs/2407.11585 (2024) - [i76]Yushi Huang, Ruihao Gong, Xianglong Liu, Jing Liu, Yuhang Li, Jiwen Lu, Dacheng Tao:
Temporal Feature Matters: A Framework for Diffusion Model Quantization. CoRR abs/2407.19547 (2024) - [i75]Aishan Liu, Yuguang Zhou, Xianglong Liu, Tianyuan Zhang, Siyuan Liang, Jiakai Wang, Yanjun Pu, Tianlin Li, Junqi Zhang, Wenbo Zhou, Qing Guo, Dacheng Tao:
Compromising Embodied Agents with Contextual Backdoor Attacks. CoRR abs/2408.02882 (2024) - 2023
- [j59]Xianglong Liu, Shihao Bai, Shan An, Shuo Wang, Wei Liu, Xiaowei Zhao, Yuqing Ma:
A meaningful learning method for zero-shot semantic segmentation. Sci. China Inf. Sci. 66(11) (2023) - [j58]Shan An, Jianye Chen, Zhaoqi Zhu, Fangru Zhou, Yuxing Yang, Yuqing Ma, Xianglong Liu, Haogang Zhu:
ARCosmetics: a real-time augmented reality cosmetics try-on system. Frontiers Comput. Sci. 17(4): 174706 (2023) - [j57]Haotong Qin, Xiangguo Zhang, Ruihao Gong, Yifu Ding, Yi Xu, Xianglong Liu:
Distribution-Sensitive Information Retention for Accurate Binary Neural Network. Int. J. Comput. Vis. 131(1): 26-47 (2023) - [j56]Yongkang Zhang, Jun Li, Na Jiang, Guoming Wu, Han Zhang, Zhi-Ping Shi, Zhaoxun Liu, Zizhang Wu, Xianglong Liu:
Temporal Transformer Networks With Self-Supervision for Action Recognition. IEEE Internet Things J. 10(14): 12999-13011 (2023) - [j55]Guoming Wu, Yangfan Xu, Jun Li, Zhi-Ping Shi, Xianglong Liu:
Imperceptible Adversarial Attack With Multigranular Spatiotemporal Attention for Video Action Recognition. IEEE Internet Things J. 10(20): 17785-17796 (2023) - [j54]Haibo Jin, Ruoxi Chen, Haibin Zheng, Jinyin Chen, Yao Cheng, Yue Yu, Tieming Chen, Xianglong Liu:
Excitement surfeited turns to errors: Deep learning testing framework based on excitable neurons. Inf. Sci. 637: 118936 (2023) - [j53]Haotong Qin, Yifu Ding, Xiangguo Zhang, Jiakai Wang, Xianglong Liu, Jiwen Lu:
Diverse Sample Generation: Pushing the Limit of Generative Data-Free Quantization. IEEE Trans. Pattern Anal. Mach. Intell. 45(10): 11689-11706 (2023) - [j52]Jun Guo, Wei Bao, Jiakai Wang, Yuqing Ma, Xinghai Gao, Gang Xiao, Aishan Liu, Jian Dong, Xianglong Liu, Wenjun Wu:
A comprehensive evaluation framework for deep model robustness. Pattern Recognit. 137: 109308 (2023) - [j51]Zhilei Li, Jun Li, Yuqing Ma, Rui Wang, Zhi-Ping Shi, Yifu Ding, Xianglong Liu:
Spatio-Temporal Adaptive Network With Bidirectional Temporal Difference for Action Recognition. IEEE Trans. Circuits Syst. Video Technol. 33(9): 5174-5185 (2023) - [j50]Yuqing Ma, Xianglong Liu, Shihao Bai, Lei Wang, Aishan Liu, Dacheng Tao, Edwin R. Hancock:
Regionwise Generative Adversarial Image Inpainting for Large Missing Areas. IEEE Trans. Cybern. 53(8): 5226-5239 (2023) - [j49]Xiaowei Zhao, Xianglong Liu, Yuqing Ma, Shihao Bai, Yifan Shen, Zeyu Hao, Aishan Liu:
Temporal Speciation Network for Few-Shot Object Detection. IEEE Trans. Multim. 25: 8267-8278 (2023) - [j48]Yisong Xiao, Aishan Liu, Tianyuan Zhang, Haotong Qin, Jinyang Guo, Xianglong Liu:
RobustMQ: benchmarking robustness of quantized models. Vis. Intell. 1(1) (2023) - [c110]Chunyu Sun, Chenye Xu, Chengyuan Yao, Siyuan Liang, Yichao Wu, Ding Liang, Xianglong Liu, Aishan Liu:
Improving Robust Fariness via Balance Adversarial Training. AAAI 2023: 15161-15169 - [c109]Jinyang Guo, Jiaheng Liu, Zining Wang, Yuqing Ma, Ruihao Gong, Ke Xu, Xianglong Liu:
Adaptive Contrastive Knowledge Distillation for BERT Compression. ACL (Findings) 2023: 8941-8953 - [c108]Aishan Liu, Shiyu Tang, Siyuan Liang, Ruihao Gong, Boxi Wu, Xianglong Liu, Dacheng Tao:
Exploring the Relationship Between Architectural Design and Adversarially Robust Generalization. CVPR 2023: 4096-4107 - [c107]Yuqing Ma, Hainan Li, Zhange Zhang, Jinyang Guo, Shanghang Zhang, Ruihao Gong, Xianglong Liu:
Annealing-based Label-Transfer Learning for Open World Object Detection. CVPR 2023: 11454-11463 - [c106]Simin Li, Shuning Zhang, Gujun Chen, Dong Wang, Pu Feng, Jiakai Wang, Aishan Liu, Xin Yi, Xianglong Liu:
Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks. CVPR 2023: 12324-12333 - [c105]Xiuying Wei, Yunchen Zhang, Yuhang Li, Xiangguo Zhang, Ruihao Gong, Jinyang Guo, Xianglong Liu:
Outlier Suppression+: Accurate quantization of large language models by equivalent and effective shifting and scaling. EMNLP 2023: 1648-1665 - [c104]Ying Li, Jingzhuo Liang, Gui Shi Jie, Yangdong Liu, Wei Huang, Yue Yan, Xianglong Liu:
An innovative experimental teaching method of hardware-software co-design-Taking a hardware accelerator of neural network using FPGA. FIE 2023: 1-5 - [c103]Haotong Qin, Mingyuan Zhang, Yifu Ding, Aoyu Li, Zhongang Cai, Ziwei Liu, Fisher Yu, Xianglong Liu:
BiBench: Benchmarking and Analyzing Network Binarization. ICML 2023: 28351-28388 - [c102]Yisong Xiao, Aishan Liu, Tianlin Li, Xianglong Liu:
Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing. ISSTA 2023: 829-841 - [c101]Yan Wang, Yuhang Li, Ruihao Gong, Aishan Liu, Yanfei Wang, Jian Hu, Yongqiang Yao, Yunchen Zhang, Tianzi Xiao, Fengwei Yu, Xianglong Liu:
SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency. MLSys 2023 - [c100]Jun Guo, Xingyu Zheng, Aishan Liu, Siyuan Liang, Yisong Xiao, Yichao Wu, Xianglong Liu:
Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks. ACM Multimedia 2023: 4178-4189 - [c99]Haotong Qin, Lei Ke, Xudong Ma, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Xianglong Liu, Fisher Yu:
BiMatting: Efficient Video Matting via Binarization. NeurIPS 2023 - [c98]Haotong Qin, Yulun Zhang, Yifu Ding, Yifan Liu, Xianglong Liu, Martin Danelljan, Fisher Yu:
QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution. NeurIPS 2023 - [c97]Chengtao Lv, Jinyang Guo, Jiaqi Yu, Ruiyan Zhang, Xianglong Liu:
CDMNet: Contrastive Distribution Mapped Network for Infrared Small Target Detection. UAVM 2023: 63-67 - [c96]Aishan Liu, Jun Guo, Jiakai Wang, Siyuan Liang, Renshuai Tao, Wenbo Zhou, Cong Liu, Xianglong Liu, Dacheng Tao:
X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection. USENIX Security Symposium 2023: 3781-3798 - [i74]Haotong Qin, Mingyuan Zhang, Yifu Ding, Aoyu Li, Zhongang Cai, Ziwei Liu, Fisher Yu, Xianglong Liu:
BiBench: Benchmarking and Analyzing Network Binarization. CoRR abs/2301.11233 (2023) - [i73]Simin Li, Jun Guo, Jingqiao Xiu, Pu Feng, Xin Yu, Jiakai Wang, Aishan Liu, Wenjun Wu, Xianglong Liu:
Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence. CoRR abs/2302.03322 (2023) - [i72]Aishan Liu, Jun Guo, Jiakai Wang, Siyuan Liang, Renshuai Tao, Wenbo Zhou, Cong Liu, Xianglong Liu, Dacheng Tao:
X-Adv: Physical Adversarial Object Attacks against X-ray Prohibited Item Detection. CoRR abs/2302.09491 (2023) - [i71]Yifu Ding, Haotong Qin, Qinghua Yan, Zhenhua Chai, Junjie Liu, Xiaolin Wei, Xianglong Liu:
Towards Accurate Post-Training Quantization for Vision Transformer. CoRR abs/2303.14341 (2023) - [i70]Xiuying Wei, Yunchen Zhang, Yuhang Li, Xiangguo Zhang, Ruihao Gong, Jinyang Guo, Xianglong Liu:
Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling. CoRR abs/2304.09145 (2023) - [i69]Yisong Xiao, Aishan Liu, Tianlin Li, Xianglong Liu:
Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing. CoRR abs/2305.11602 (2023) - [i68]Simin Li, Shuing Zhang, Gujun Chen, Dong Wang, Pu Feng, Jiakai Wang, Aishan Liu, Xin Yi, Xianglong Liu:
Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attacks. CoRR abs/2305.12863 (2023) - [i67]Simin Li, Jun Guo, Jingqiao Xiu, Xini Yu, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu:
Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game. CoRR abs/2305.12872 (2023) - [i66]Yan Wang, Yuhang Li, Ruihao Gong, Aishan Liu, Yanfei Wang, Jian Hu, Yongqiang Yao, Yunchen Zhang, Tianzi Xiao, Fengwei Yu, Xianglong Liu:
SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency. CoRR abs/2307.00280 (2023) - [i65]Jun Guo, Aishan Liu, Xingyu Zheng, Siyuan Liang, Yisong Xiao, Yichao Wu, Xianglong Liu:
Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks. CoRR abs/2308.00958 (2023) - [i64]Yisong Xiao, Aishan Liu, Tianyuan Zhang, Haotong Qin, Jinyang Guo, Xianglong Liu:
RobustMQ: Benchmarking Robustness of Quantized Models. CoRR abs/2308.02350 (2023) - [i63]Wei Huang, Haotong Qin, Yangdong Liu, Jingzhuo Liang, Yifu Ding, Ying Li, Xianglong Liu:
OHQ: On-chip Hardware-aware Quantization. CoRR abs/2309.01945 (2023) - [i62]Simin Li, Ruixiao Xu, Jun Guo, Pu Feng, Jiakai Wang, Aishan Liu, Yaodong Yang, Xianglong Liu, Weifeng Lv:
MIR2: Towards Provably Robust Multi-Agent Reinforcement Learning by Mutual Information Regularization. CoRR abs/2310.09833 (2023) - [i61]Zhuoyi Zhang, Yunchen Zhang, Gonglei Shi, Yu Shen, Ruihao Gong, Xiaoxu Xia, Qi Zhang, Lewei Lu, Xianglong Liu:
Exploring the Potential of Flexible 8-bit Format: Design and Algorithm. CoRR abs/2310.13513 (2023) - [i60]Jiakai Wang, Donghua Wang, Jin Hu, Siyang Wu, Tingsong Jiang, Wen Yao, Aishan Liu, Xianglong Liu:
Adversarial Examples in the Physical World: A Survey. CoRR abs/2311.01473 (2023) - [i59]Yushi Huang, Ruihao Gong, Jing Liu, Tianlong Chen, Xianglong Liu:
TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models. CoRR abs/2311.16503 (2023) - [i58]Aishan Liu, Xinwei Zhang, Yisong Xiao, Yuguang Zhou, Siyuan Liang, Jiakai Wang, Xianglong Liu, Xiaochun Cao, Dacheng Tao:
Pre-trained Trojan Attacks for Visual Recognition. CoRR abs/2312.15172 (2023) - 2022
- [j47]Aishan Liu, Huiyuan Xie, Xianglong Liu, Zixin Yin, Shunchang Liu:
Revisiting audio visual scene-aware dialog. Neurocomputing 496: 227-237 (2022) - [j46]Jun Li, Duorui Wang, Xianglong Liu, Zhi-Ping Shi, Meng Wang:
Two-Branch Attention Network via Efficient Semantic Coupling for One-Shot Learning. IEEE Trans. Image Process. 31: 341-351 (2022) - [j45]Jiakai Wang, Aishan Liu, Xiao Bai, Xianglong Liu:
Universal Adversarial Patch Attack for Automatic Checkout Using Perceptual and Attentional Bias. IEEE Trans. Image Process. 31: 598-611 (2022) - [j44]Yuqing Ma, Shihao Bai, Wei Liu, Shuo Wang, Yue Yu, Xiao Bai, Xianglong Liu, Meng Wang:
Transductive Relation-Propagation With Decoupling Training for Few-Shot Learning. IEEE Trans. Neural Networks Learn. Syst. 33(11): 6652-6664 (2022) - [c95]Shunchang Liu, Jiakai Wang, Aishan Liu, Yingwei Li, Yijie Gao, Xianglong Liu, Dacheng Tao:
Harnessing Perceptual Adversarial Patches for Crowd Counting. CCS 2022: 2055-2069 - [c94]Lei Huang, Yi Zhou, Tian Wang, Jie Luo, Xianglong Liu:
Delving into the Estimation Shift of Batch Normalization in a Network. CVPR 2022: 753-762 - [c93]Jiakai Wang, Zixin Yin, Pengfei Hu, Aishan Liu, Renshuai Tao, Haotong Qin, Xianglong Liu, Dacheng Tao:
Defensive Patches for Robust Recognition in the Physical World. CVPR 2022: 2446-2455 - [c92]Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang, Daisheng Jin, Qiang Zhou, Zhongang Cai, Haiyu Zhao, Xianglong Liu, Ziwei Liu:
Delving Deep into the Generalization of Vision Transformers under Distribution Shifts. CVPR 2022: 7267-7276 - [c91]Ye Liu, Yaya Cheng, Lianli Gao, Xianglong Liu, Qilong Zhang, Jingkuan Song:
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack. CVPR 2022: 15084-15093 - [c90]Renshuai Tao, Hainan Li, Tianbo Wang, Yanlu Wei, Yifu Ding, Bowei Jin, Hongping Zhi, Xianglong Liu, Aishan Liu:
Exploring Endogenous Shift for Cross-domain Detection: A Large-scale Benchmark and Perturbation Suppression Network. CVPR 2022: 21157-21167 - [c89]Xingrun Xing, Yangguang Li, Wei Li, Wenrui Ding, Yalong Jiang, Yufeng Wang, Jing Shao, Chunlei Liu, Xianglong Liu:
Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies. ECCV (11) 2022: 536-552 - [c88]Yuyang Long, Qilong Zhang, Boheng Zeng, Lianli Gao, Xianglong Liu, Jian Zhang, Jingkuan Song:
Frequency Domain Model Augmentation for Adversarial Attack. ECCV (4) 2022: 549-566 - [c87]Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu:
BiBERT: Accurate Fully Binarized BERT. ICLR 2022 - [c86]Xiuying Wei, Ruihao Gong, Yuhang Li, Xianglong Liu, Fengwei Yu:
QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization. ICLR 2022 - [c85]Haotong Qin, Xudong Ma, Yifu Ding, Xiaoyang Li, Yang Zhang, Yao Tian, Zejun Ma, Jie Luo, Xianglong Liu:
BiFSMN: Binary Neural Network for Keyword Spotting. IJCAI 2022: 4346-4352 - [c84]Yan Wu, Xiaowei Zhao, Yuqing Ma, Duorui Wang, Xianglong Liu:
Two-branch Objectness-centric Open World Detection. HCMA@MM 2022: 35-40 - [c83]Renshuai Tao, Tianbo Wang, Ziyang Wu, Cong Liu, Aishan Liu, Xianglong Liu:
Few-shot X-ray Prohibited Item Detection: A Benchmark and Weak-feature Enhancement Network. ACM Multimedia 2022: 2012-2020 - [c82]Yuxuan Wang, Jiakai Wang, Zixin Yin, Ruihao Gong, Jingyi Wang, Aishan Liu, Xianglong Liu:
Generating Transferable Adversarial Examples against Vision Transformers. ACM Multimedia 2022: 5181-5190 - [c81]Yifu Ding, Haotong Qin, Qinghua Yan, Zhenhua Chai, Junjie Liu, Xiaolin Wei, Xianglong Liu:
Towards Accurate Post-Training Quantization for Vision Transformer. ACM Multimedia 2022: 5380-5388 - [c80]Xiuying Wei, Yunchen Zhang, Xiangguo Zhang, Ruihao Gong, Shanghang Zhang, Qi Zhang, Fengwei Yu, Xianglong Liu:
Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models. NeurIPS 2022 - [i57]Xiaowei Zhao, Xianglong Liu, Yifan Shen, Yixuan Qiao, Yuqing Ma, Duorui Wang:
Revisiting Open World Object Detection. CoRR abs/2201.00471 (2022) - [i56]Haotong Qin, Xudong Ma, Yifu Ding, Xiaoyang Li, Yang Zhang, Yao Tian, Zejun Ma, Jie Luo, Xianglong Liu:
BiFSMN: Binary Neural Network for Keyword Spotting. CoRR abs/2202.06483 (2022) - [i55]Junchi Yan, Xianglong Liu, Ruoyu Cheng, Yibo Lin:
Towards Machine Learning for Placement and Routing in Chip Design: a Methodological Overview. CoRR abs/2202.13564 (2022) - [i54]