Publications
2025
Haiming Xu, Qi Chen, Lei Wang, Lingqiao Liu*, Attention-driven GUI Grounding: Leveraging Pretrained Multimodal Large Language Models without Fine-Tuning. AAAI 2025.
Jiatong Xia, Libo Sun, Lingqiao Liu*, Enhancing Close-up Novel View Synthesis via Pseudo-labeling. AAAI 2025.
2024
Xuan Ren, Biao Wu, Lingqiao Liu*, I Learn Better If You Speak My Language: Understanding the Superior Performance of Fine-Tuning Large Language Models with LLM-Generated Responses. EMNLP 2024 [C68]
Zihu Wang, Lingqiao Liu, Scott Ricardo Figueroa Weston, Samuel Tian, Peng Li. On Learning Discriminative Features from Synthesized Data for Self-Supervised Fine-Grained Visual Recognition ECCV 2024 [C67]
Yingshu Li, Zhanyu Wang, Yunyi Liu, Lei Wang, Lingqiao Liu, Luping Zhou, KARGEN: Knowledge-enhanced Automated Radiology Report Generation Using Large Language Models, MICCAI 2024 [C66]
Yunyi Liu, Zhanyu Wang, Yingshu Li, Xinyu Liang, Lingqiao Liu, Lei Wang, Luping Zhou, MRScore: Evaluating Medical Report with LLM-based Reward System. MICCAI 2024 [C65]
Minh Hieu Phan, Yutong Xie, Yuankai Qi, Lingqiao Liu, Liyang Liu, Bowen Zhang, Zhibin Liao, Qi Wu, Minh-Son To, Johan W. Verjans, “Decomposing Disease Descriptions for Enhanced Pathology Detection: A Multi-Aspect Vision-Language Matching Framework”, CVPR 2024 [C64]
Ziqin Zhou, Haiming Xu, Yangyang Shu, Lingqiao Liu*, Unlocking the Potential of Pre-trained Vision Transformers for Few-Shot Semantic Segmentation through Relationship Descriptors. CVPR 2024 [C63]
2023
Yutong Xie, Jianpeng Zhang, Lingqiao Liu, Hu Wang, Yiwen Ye, Verjans Johan, Yong Xia, ReFs: A Hybrid Pre-training Paradigm for 3D Medical Image Segmentation, Medical Image Analysis 2023.[J28]
Bingliang Jiao, Lingqiao Liu, Liying Gao, Guosheng Lin, Peng Wang, Yanning Zhang: Toward Re-Identifying Any Animal. NeurIPS 2023 [C62]
Yuxuan Ding, Chunna Tian, Haoxuan Ding, Lingqiao Liu*: The CLIP Model is Secretly an Image-to-Prompt Converter. NeurIPS 2023 [C61]
Lin Wu, Lingqiao Liu, Yang Wang, Zheng Zhang, Farid Boussaid, Mohammed Bennamoun: Learning Resolution-Adaptive Representations for Cross-Resolution Person Re-Identification. IEEE Transcation on Image Processing 2023 [J27]
Xizhe Xue, Dongdong Yu, Lingqiao Liu, Yu Liu, Satoshi Tsutsui, Ying Li, Zehuan Yuan, Ping Song, Mike Zheng Shou: Transformer-based Open-world Instance Segmentation with Cross-task Consistency Regularization. ACM MM 2023 [C60]
Liang Chen, Yong Zhang, Yibin Song, Anton van den Hengel, Lingqiao Liu*: Domain Generalization via Rationale Invariance. ICCV 2023 [C59]
Ziqin Zhou, Yinjie Lei, Bowen Zhang, Lingqiao Liu*, Yifan liu: ZegCLIP: Towards Adapting CLIP for Zero-shot Semantic Segmentation. CVPR 2023 [C58]
Yangyang Shu, Anton van den Hengel, Lingqiao Liu*: Learning Common Rationale to Improve Self-Supervised Representation for Fine-Grained Visual Recognition Problems. CVPR 2023 [C57]
Liang Chen, Yong Zhang, Yibing Song, Ying Shan, Lingqiao Liu*: Improved Test-Time Adaptation for Domain Generalization. CVPR 2023 [C56]
Zhanyu Wang, Lingqiao Liu, Lei Wang, Luping Zhou: METransformer: Radiology Report Generation by Transformer with Multiple Expert Learners. CVPR 2023 [C55]
Qingsheng Wang, Lingqiao Liu, Chenchen Jing, Hao Chen, Guoqiang Liang, PENG WANG, Chunhua Shen: Learning Conditional Attributes for Compositional Zero-Shot Learning. CVPR 2023 [C54]
2022
Qiaoyang Luo, Lingqiao Liu*: Zero-shot Slot Filling with Slot-Prefix Prompting and Attention Relationship Descriptor. AAAI 2023 [C53]
Avraham Chapman, Lingqiao Liu: Regularizing Neural Network Training via Identity-wise Discriminative Feature Suppression. DICTA 2022 [C52]
Haiming Xu, Hao Chen, Yufei Yin, Lingqiao Liu: Dual Decision Improves Open-Set Panoptic Segmentation. BMVC 2022 [C51]
Liang Chen, Yong Zhang, Yibing Song, Jue Wang, Lingqiao Liu*: OST: Improving Generalization of DeepFake Detection via One-Shot Test-Time Training. NeurIPS 2022. [C50]
Haiming Xu, Lingqiao Liu*, Qiuchen Bian, Zhen Yang: Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization. NeurIPS 2022 [C49]
Lu Yang, Yunlong Wang, Lingqiao Liu, Peng Wang, Yanning Zhang: Center Prediction Loss for Re-identification. Pattern Recognition. Available online 28 July 2022, 108949 [J27]
Yangyang Shu, Baosheng Yu, Haiming Xu, Lingqiao Liu*: Improving Fine-grained Visual Recognition in Low Data Regimes via Self-boosting Attention Mechanism. ECCV 2022 Link [C48]
Bingliang Jiao, Lingqiao Liu, Liying Gao, Guosheng Lin, Lu Yang, Shizhou Zhang, Peng Wang, Yanning Zhang: Dynamically Transformed Instance Normalization Network for Generalizable Person Re-identification. ECCV 2022 [C47]
Yingjie Zhou, Xucheng Song, Yanru Zhang, Fanxing Liu, Ce Zhu, Lingqiao Liu*: Feature Encoding With Autoencoders for Weakly Supervised Anomaly Detection. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2454-2465 (2022) [J26]
Lu Yang, Hongbang Liu, Lingqiao Liu, Jinghao Zhou, Lei Zhang, Peng Wang, Yanning Zhang:Pluggable Weakly-Supervised Cross-View Learning for Accurate Vehicle Re-Identification. ICMR 2022: 81-89 [C46]
Liang Chen, Yong Zhang, Yibing Song, Lingqiao Liu*, Jue Wang: Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection. CVPR 2022 (Oral) Link [C45]
Hai-Ming Xu, Lingqiao Liu*, Ehsan Abbasnejad: Progressive Class Semantic Matching for Semi-supervised Text Classification. NAACL-HLT 2022: 3003-3013 2022 (Oral) Link [C44]
Bohan Zhuang, Chunhua Shen, Mingkui Tan, Peng Chen, Lingqiao Liu, Ian Reid: Structured Binary Neural Networks for Image Recognition. IJCV (Accepted in 2022) [J26]
2021
Junjie Zhang, Lingqiao Liu, Peng Wang, Jian Zhang: Exploring the auxiliary learning for long-tailed visual recognition. Neurocomputing 449: 303-314 (2021) [J25]
Liangyi Kang, Jie Liu, Lingqiao Liu, Zhiyang Zhou, Dan Ye: Semi-supervised emotion recognition in textual conversation via a context-augmented auxiliary training task. Inf. Process. Manag. 58(6): 102717 (2021) [J24]
Yinjie Lei, Yan Liu, Pingping Zhang, Lingqiao Liu*: Towards using count-level weak supervision for crowd counting. Pattern Recognit. 109: 107616 (2021) [J23]
Wanxuan Lu, Dong Gong, Kun Fu, Xian Sun, Wenhui Diao, Lingqiao Liu*: Boundarymix: Generating pseudo-training images for improving segmentation with scribble annotations. Pattern Recognit. 117: 107924 (2021) [J22]
Haibo Su, Peng Wang, Lingqiao Liu, Hui Li, Zhen Li, Yanning Zhang: Where to Look and How to Describe: Fashion Image Retrieval With an Attentional Heterogeneous Bilinear Network. IEEE Trans. Circuits Syst. Video Technol. 31(8): 3254-3265 (2021) [J21]
Duo Peng, Yinjie Lei, Lingqiao Liu, Pingping Zhang, Jun Liu: Global and Local Texture Randomization for Synthetic-to-Real Semantic Segmentation. IEEE Trans. Image Process. 30: 6594-6608 (2021) [J20]
Qiaoyang Luo, Lingqiao Liu*, Yuhao Lin, Wei Zhang: Don’t Miss the Labels: Label-semantic Augmented Meta-Learner for Few-Shot Text Classification. ACL/IJCNLP (Findings) 2021: 2773-2782 [c42]
Hai-Ming Xu, Lingqiao Liu*, Dong Gong: Semi-supervised Learning via Conditional Rotation Angle Estimation. DICTA 2021: 1-8 [C41]
Liangyi Kang, Jie Liu, Lingqiao Liu, Dan Ye: Label Definitions Augmented Interaction Model for Legal Charge Prediction. ECIR (1) 2021: 270-283 [C40]
Yanjie Gou, Yinjie Lei, Lingqiao Liu, Yong Dai, Chunxu Shen: Contextualize Knowledge Bases with Transformer for End-to-end Task-Oriented Dialogue Systems. EMNLP (1) 2021: 4300-4310 [C39]
2020
Yan Liu, Lingqiao Liu, Peng Wang, Pingping Zhang, Yinjie Lei. Semi-supervised Crowd Counting via Self-training on Surrogate Tasks. ECCV 2020. [C38]
Yu Liu, Lingqiao Liu, Haokui Zhang, S. Hamid Rezatofighi, Qingsen Yan, Ian Reid. Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems. [C37]
Yanjie Gou, Yinjie Lei, Lingqiao Liu, Pingping Zhang, Xi Peng. A Dynamic Parameter Enhanced Network for distant supervised relation extraction. Knowledge-Based Systems 2020. [J19]
Zhibin Liao, Lingqiao Liu, Qi Wu, Damien Teney, Chunhua Shen, Anton van den Hengel, Johan Verjans. Medical Data Inquiry Using a Question Answering Model. 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). [C36]
Lei Zhang, Peng Wang, Lingqiao Liu, Chunhua Shen,Wei Wei, Yanning Zhang, Anton Van Den Hengel. Towards effective deep embedding for zero-shot learning. IEEE Transactions on Circuits and Systems for Video Technology 2020. [J18]
Lei Zhang, Peng Wang, Chunhua Shen, Lingqiao Liu, Wei Wei, Yanning Zhang, Anton Van Den Hengel. Adaptive importance learning for improving lightweight image super-resolution network. International Journal of Computer Vision, 2020. [J17]
Bohan Zhuang, Lingqiao Liu, Mingkui Tan, Chunhua Shen, Ian Reid. Training Quantized Neural Networks with the Full-precision Auxiliary Module.IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [C35]
Damien Teney, Peng Wang, Jiewei Cao, Lingqiao Liu, Chunhua Shen, Anton van den Hengel. V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices. AAAI 2020. [C34]
2019
Yinjie Lei, Ziqin Zhou, Pingping Zhang, Yulan Guo, ZijunMa, Lingqiao Liu. Deep point-to-subspace metric learning for sketch-based 3D shape retrieval. Pattern Recognition, 2019. [J16]
Shengqin Jiang, Xiaobo Lu, Lingqiao Liu. Mask-aware networks for crowd counting. IEEE Transactions on Circuits and Systems for Video Technology. 2019. [J15]
Dong Gong, Lingqiao Liu, Vuong Le, Budhaditya Saha, Moussa Reda Mansour, Svetha Venkatesh, Anton van den Hengel. Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection. IEEE International Conference on Computer Vision (ICCV) 2019. [C33]
Xiu-Shen Wei, Peng Wang, Lingqiao Liu, Chunhua Shen, Jianxin Wu. Piecewise classifier mappings:Learning fine-grained learners for novel categories with few examples. IEEE Transactions on Image Processing, Accepted in May 2019. [J14]
Ehsan Abbasnejad, Javen Shi, Anton van den Hengel, Lingqiao Liu. A Generative Adversarial Density Estimator. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR ), 2019. [C32]
Bohan Zhuang, Chunhua Shen, Mingkui Tan, Lingqiao Liu, Ian Reid. Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [C31]
Peng Wang,Lingqiao Liu, Chunhua Shen, Heng Tao Shen. Order-Aware Convolutional Pooling for Video Based Action Recognition, Pattern Recognition (PR) 2019. [J14]
Yu Chen, Chunhua Shen, Hao Chen, Xiu-Shen Wei, Lingqiao Liu, Jian Yang. Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization, IEEE Transcation Pattern Analysis and Machine Intelligence. Accepted in 2019 . [J13]
2018
Jie Yang, Dong Gong, Lingqiao Liu, Qinfeng Shi. Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal. In European Conference on Computer Vision (ECCV), 2018. [C30]
Zetao Chen, Lingqiao Liu, Inkyu Sa, Zongyuan Ge, Margarita Chli, Learning Context Flexible Attention Model for Long-term Visual Place Recognition. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2018 . [C29]
Bohan Zhuang, Chunhua Shen, Mingkui Tan, Lingqiao Liu, Ian Reid, Towards effective low-bitwidth convolutional neural networks. Computer Vision and Pattern Recognition (CVPR) 2018 . [C28]
2017
Bohan Zhuang, Lingqiao Liu, Chunhua Shen, Ian Reid. Towards Context-aware Interaction Recognition for Visual Relationship Detection. IEEE International Conference on Computer Vision (ICCV) 2017. (* Indicates equal contribution.) [C27]
Tong Shen, Guosheng Lin, Lingqiao Liu, Chunhua Shen, Ian Reid. Weakly Supervised Semantic Segmentation Based on Co-segmentation . British Machine Vision Conference (BMVC) 2017. [C26]
Ruizhi Qiao, Lingqiao Liu, Chunhua Shen, Anton van den Hengel. Visually Aligned Word Embeddings for Improving Zero-shot Learning. (ORAL)British Machine Vision Conference (BMVC) 2017. [C25]
Yao Li, Guosheng Lin, Bohan Zhuang, Lingqiao Liu, Chunhua Shen, Anton van den Hengel. Sequential Person Recognition in Photo Albums with a Recurrent Network. Computer Vision and Pattern Recognition (CVPR) 2017. [C24]
Damien Teney, Lingqiao Liu, Anton van den Hengel. Graph-Structured Representations for Visual Question Answering. Computer Vision and Pattern Recognition (CVPR) 2017. [C23]
Bohan Zhuang, Lingqiao Liu, Chunhua Shen, Ian Reid. Attend in groups: a weakly-supervised deep learning framework for learning from web data. Computer Vision and Pattern Recognition (CVPR) 2017. (* Indicates equal contribution.) [C22]
Peng Wang, Lingqiao Liu, Chunhua Shen, Zi Huang, Anton van den Hengel, Heng Tao Shen, Multi-attention Network for One Shot Learning.Computer Vision and Pattern Recognition (CVPR) 2017. (* Indicates equal contribution.) [C21]
Dong Gong, Jie Yang, Lingqiao Liu, Yanning Zhang, Ian Reid, Chunhua Shen, Anton van den Hengel, Qinfeng Shi. From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blur. Computer Vision and Pattern Recognition (CVPR) 2017. [C20]
Zetao Chen, Adam Jacobson, Niko Sünderhauf, Ben Upcroft, Lingqiao Liu, Chunhua Shen, Ian Reid, Michael Milford, Deep Learning Features at Scale for Visual Place Recognition. International Conference on Robotics and Automation (ICRA). 2017 [C19]
2016
Ruizhi Qiao, Lingqiao Liu, Chunhua Shen, Anton van den Hengel. Learning discriminative trajectorylet detector sets for accurate skeleton-based action recognition. Pattern Recognition. Accepted in 2016 [J12]
ZongYuan Ge, Chris McCool, Conrad Sanderson, Peng Wang, Lingqiao Liu, Ian D. Reid, Peter I. Corke, Exploiting Temporal Information for DCNN-Based Fine-Grained Object Classification. DICTA 2016. [C18]
Lingqiao Liu, Peng Wang, Chunhua Shen, Lei Wang, Anton van den Hengel, Chao Wang, Hengtao Shen. Compositional Model based Fisher Vector Coding for Image Classification. IEEE Transcation Pattern Analysis and Machine Intelligence. Accepted in 2016 (* Indicates equal contribution.) [J11]
Lingqiao Liu, Chunhua Shen, Anton van den Hengel. Cross-convolutional-layer Pooling for Image Recognitions. IEEE Transcation Pattern Analysis and Machine Intelligence. Accepted in 2016 [J10]
Yao Li, Lingqiao Liu, Chunhua Shen, Anton van den Hengel. Mining Mid-level Visual Patterns with Deep CNN Activations. International Journal on Computer Vision (IJCV), 2016 (* Indicates equal contribution.) [J9]
Yao Li, Lingqiao Liu, Chunhua Shen, Anton van den Hengel. Image Co-localization by Mimicking a Good Detector’s Confidence Score Distribution. European Conference on Computer Vision (ECCV), 2016. (* Indicates equal contribution.) [c17]
Peng Wang, Lingqiao Liu, Chunhua Shen, Zi Huang, Anton van den Hengel, Heng Tao Shen.What’s Wrong with that Object? Identifying Images of Unusual Objects by Modelling the Detection Score Distribution. Computer Vision and Pattern Recognition (CVPR) 2016. (* Indicates equal contribution.) [c16]
Ruizhi Qiao, Lingqiao Liu, Chunhua Shen, Anton van den Hengel. Less is More: Zero-shot Learning from Online Textual Documents with Noise Suppression Mechanism. Computer Vision and Pattern Recognition (CVPR) 2016. (* Indicates equal contribution.) [c15]
Qi Wu, Chunhua Shen, Anton van den Hengel, Lingqiao Liu, Anthony Dick. What value high level concepts in vision to language problems? Computer Vision and Pattern Recognition (CVPR) 2016. [c14]
Peng Wang, Yuanzhouhan Cao, Chunhua Shen, Lingqiao Liu, HengTao Shen. Temporal Pyramid Pooling Based Convolutional Neural Network for Action Recognition. IEEE Transactions on Circuits and Systems for Video Technology. Accepted in 2016 [J8]
2015
Lei Wang, Lingqiao Liu, and Luping Zhou, A Graph-embedding Approach to Hierarchical Visual Word Mergence, IEEE Transactions on Neural Networks and Learning Systems, Accepted in Dec 2015. [J7]
Luping Zhou, Lei Wang, Lingqiao Liu, Philip Ogunbona, and Dinggang Shen, Learning Discriminative Bayesian Networks from High-dimensional Continuous Neuroimaging Data, IEEE Transactions on Pattern Analysis and Machine Intelligence, Accepted in Nov 2015. [J6]
Lingqiao Liu, Lei Wang, Chunhua Shen, A generalized probabilistic framework for compact codebook creation, IEEE Transcation Pattern Analysis and Machine Intelligence. Accepted in April 2015 [J5]
Chao Wang, Lei Wang, Lingqiao Liu, Density Maximization for Improving Graph Matching with Its Applications, IEEE Transactions on Image Processing, Accepted in March 2015. [J4]
Lingqiao Liu, Chunhua Shen, Anton van den Hengel. The Treasure beneath Convolutional Layers: Cross-convolutional-layer Pooling for Image Classification. Computer Vision and Pattern Recognition (CVPR) 2015. [c13]
Yao Li, Lingqiao Liu, Chunhua Shen, Anton van den Hengel. Mid-level Deep Pattern Mining, Computer Vision and Pattern Recognition (CVPR) 2015. (* Indicates equal contribution.) [c12]
2014
Lei Wang, Lingqiao Liu, Luping Zhou, KL Chan. Application of SVMs to the Bag-of-Features Model: A Kernel Perspective, In Support Vector Machines Applications, pp 155-189. Published by Springer in January 2014. [B1]
Lingqiao Liu, Lei Wang. HEp-2 cell image classification with multiple linear descriptors, Pattern Recognition, Vol 47(7): 2400-2408, 2014 [J3]
Lei Wang, Luping Zhou, Chunhua Shen, Lingqiao Liu, Huan Liu. A Hierarchical Word-Merging Algorithm with Class Separability Measure, IEEE Transcation Pattern Analysis and Machine Intelligence. Vol.36(3): 417-435, 2014 [J2]
Lingqiao Liu, Chunhua Shen, Lei Wang, Anton van den Hengel, Chao Wang. Encoding high-dimensional local features by sparse coding based fisher vectors, Advances in Neural Information Processing Systems (NIPS) 2014, pp 1143-1151, June 2014. [c11]
Chao Wang, Lei Wang, Lingqiao Liu, Progressive Mode-Seeking on Graphs for Sparse Feature Matching, European Conference on Computer Vision (ECCV), pp 788-802, 2014 [c10]
Luping Zhou, Lei Wang, Lingqiao Liu, Philip Ogunbona, Dinggang Shen. Max-Margin Based Learning for Discriminative Bayesian Network from Neuroimaging Data, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp: 321-328, 2014 [c9]
2013
Luping Zhou, Lei Wang, Lingqiao Liu, Philip Ogunbona, Dinggang Shen. Discriminative Brain Effective Connectivity Analysis for Alzheimer’s Disease: A Kernel Learning Approach upon Sparse Gaussian Bayesian Network, Computer Vision and Pattern Recognition (CVPR) 2013, pp 2243-2250. [c8]
Jianjia Zhang, Lei Wang, Lingqiao Liu, Luping Zhou, Wanqing Li. Accelerating the Divisive Information-Theoretic Clustering of Visual Words, The International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2013, pp 1-8. [c7]
Lingqiao Liu, Lei Wang. A Scalable Unsupervised Feature Merging Approach to Efficient Dimensionality Reduction of High Dimensional Visual Data, IEEE International Conference on Computer Vision (ICCV), 2013. pp 3008-3015 [c6]
Chao Wang, Lei Wang, Lingqiao Liu. Improving Graph Matching via Density Maximization, 2013 IEEE International Conference on Computer Vision (ICCV), 2013. pp 3424-3431 [c5]
2012
Xinwang Liu, Lei Wang, Jianping Yin, Lingqiao Liu. Incorporation of radius-info can be simple with SimpleMKL, Neurocomputing, Vol 89: 30-38, 2012 [J1]
Lingqiao Liu, Lei Wang. What has my classifier learned? Visualizing the classification rules of bag-of-feature model by support region detection, Computer Vision and Pattern Recognition (CVPR) 2012, pp 3586-3593 [c4]
2011
Lingqiao Liu, Lei Wang, Chunhua Shen. A generalized probabilistic framework for compact codebook creation, Computer Vision and Pattern Recognition (CVPR) 2011, pp 1537-1544. [c3]
Lingqiao Liu, Lei Wang, Xinwang Liu. In defense of soft-assignment coding, 2011 IEEE International Conference on Computer Vision (ICCV), pp 2486-2493. [c2]
Lingqiao Liu, Lei Wang. Exploring latent class information for image retrieval using the bag-of-feature model, ACM Multimedia 2011, pp 1405-1408. [c1]