Dr. Liang Yixiong is current a professor at the School of Computer Science, Central South University. He was selected as a "Young Backbone Teacher of Hunan Province's Ordinary Colleges and Universities" and is a third-tier talent in Central South University's 531 Talent Program. His research focuses on computer vision and machine learning, digital image/medical image processing. He holds over 20 authorized invention patents and has published more than 70 papers in prestigious top-tier conferences such as ICCV, NeurIPS, ACM MM and MICCAI, as well as in journals including PR, IEEE JBHI, IEEE/ACM TCBB, IEEE TCSVT, and ACM TIST, etc. He serves as a program committee member/reviewer for international top-tier conferences like CVPR, ICLR, NeurIPS, ICML, AAAI, ACM MM, and MICCAI, and as a reviewer for leading journals such as IEEE TIP, IEEE TMI, IEEE TC, IEEE JBHI, etc.

In 2009, he was honored as a "Young Backbone Teacher of Hunan Province's Ordinary Colleges and Universities." From July 2011 to July 2012, he conducted visiting research at the Robotics Institute, Carnegie Mellon University. 

His current research interests primarily include object detection based on multimodal learning, image semantic/instance segmentation, computer-aided screening and diagnosis, and intelligent robotics. He is responsible for teaching undergraduate courses such as "Machine Learning," "Computer Vision," "Deep Learning Technology," and "Digital Image Processing," as well as graduate courses like "Digital Image Processing and Applications."

Warmly welcomes outstanding students with a strong interest in multimodal learning, computer vision, smart healthcare, and intelligent robotics to join his research team! (Email: yxliang[at]csu[dot]edu[dot]cn;  QQ：6532695;  Mobile/WeChat: 13548670948 )

Paper-Reading-Group

Recent publications (Google Scholar, DBLP) 

[1] Yuan Liu, Zhe Qu, Shu Wang, Chengchao Shen, Yixiong Liang, and Jianxin Wang, “A Unified Personalized Federated Learning Framework Ensuring Domain Generalization,” Expert Systems with Applications, p. 125700, 2024.

[2] Haojie Zhang, Min Zeng, Jinfeng Ding, Yixiong Liang, Ruiqing Zheng, Zhe Qu, Hulin Kuang, Min Li, and Shichao Kan, “Aligning Multimodal Biomedical Images and Language via One Large Vision-Language Model,” in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024. (Accept)

[3] Bolei Chen, Jiaxu Kang, Ping Zhong, Yixiong Liang, Yu Sheng, and Jianxin Wang, “Embodied Contrastive Learning with Geometric Consistency and Behavioral Awareness for Object Navigation,” in ACM international conference on Multimedia (ACM MM), 2024, pp. 4776–4785.

[4] Lina Huang, Yixiong Liang, and Jianfeng Liu, “DES-SAM: Distillation-Enhanced Semantic SAM for Cervical Nuclear Segmentation with Box Annotation,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024, pp. 223-234.

[5] Ziyuan Ding, Yixiong Liang, Shichao Kan, and Qing Liu, “HRDecoder: High-Resolution Decoder Network for Fundus Image Lesion Segmentation,” in International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024, pp. 328-338. (Oral)

[6] Shu Wang, Zhe Qu, Yuan Liu, Shichao Kan, Yixiong Liang, and Jianxin Wang, “FedMMR: Multi-Modal Federated Learning Via Missing Modality Reconstruction,” in IEEE International Conference on Multimedia and Expo (ICME), 2024, pp. 1–6. (Best Paper Award)

[7] Qing Liu, Hailong Zeng, Zhaodong Sun, Xiaobai Li, Guoying Zhao, and Yixiong Liang, “Many Birds, One Stone: Medical Image Segmentation with Multiple Partially Labelled Datasets,” Pattern Recognition, vol. 155, p. 110636, 2024.

[8] Hailong Zeng, Jianfeng Liu, and Yixiong Liang, “Task-Aware Transformer For Partially Supervised Retinal Fundus Image Segmentation,” in International Joint Conference on Neural Networks (IJCNN), 2024, pp. 1–8.

[9] Bolei Chen, Siyi Lu, Ping Zhong, Yongzheng Cui, Yixiong Liang, and Jianxin Wang, “SemNav-HRO: A Target-Driven Semantic Navigation Strategy with Human-Robot-Object Ternary Fusion,” Engineering Applications of Artificial Intelligence, vol. 127, p. 107370, 2024.

[10] Bolei Chen, Jiaxu Kang, Ping Zhong, Yongzheng Cui, Siyi Lu, Yixiong Liang, and Jianxin Wang, “Think Holistically, Act Down-to-Earth: A Semantic Navigation Strategy with Continuous Environmental Representation and Multi-step Forward Planning,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 5, pp. 3860–3875, 2024.

[11] Chaojun Zhang, Yixiong Liang, and Qing Liu, “CCBox: Improving Box-Supervised Nuclei Segmentation with Consistency Constraint,” in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023, pp. 2412–2415.

[12] Shengqi Li, Qing Liu, Chaojun Zhang, and Yixiong Liang, “Adaptive Cluster Assignment for Unsupervised Semantic Segmentation,” in Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 2023, pp. 75--86.

[13] Hulin Kuang, Yahui Wang, Yixiong Liang, Jin Liu, and Jianxin Wang, “BEA-Net: Body and Edge Aware Network with Multi-Scale Short-Term Concatenation for Medical Image Segmentation,” IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 10, pp. 4828–4839, 2023.

[14] Lele Lv, Qing Liu, Shichao Kan, and Yixiong Liang, “Confidence-Aware Contrastive Learning for Semantic Segmentation,” in ACM international conference on Multimedia (ACM MM), 2023, pp. 5584–5593.

[15] Haotian Liu, Qing Liu, Yang Liu, Yixiong Liang, and Guoying Zhao, “Exploring Effective Knowledge Distillation for Tiny Object Detection,” in IEEE International Conference on Image Processing (ICIP), 2023, pp. 770–774.

[16] Bolei Chen, Ping Zhong, Yongzheng Cui, Siyi Lu, Yixiong Liang, and Yu Sheng, “EMExplorer: An Episodic Memory Enhanced Autonomous Exploration Strategy with Voronoi Domain Conversion and Invalid Action Masking,” Complex & Intelligent Systems, pp. 1–15, 2023.

[17] Tao Sheng, Chengchao Shen, Yuan Liu, Yeyu Ou, Zhe Qu, Yixiong Liang, and Jianxin Wang, “Modeling Global Distribution for Federated Learning with Label Distribution Skew,” Pattern Recognition, p. 109724, 2023.

[18] Yixiong Liang, Shuo Feng, Qing Liu, Hulin Kuang, Jianfeng Liu, Liyan Liao, Yun Du, and Jianxin Wang, “Exploring Contextual Relationships for Cervical Abnormal Cell Detection,” IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 8, pp. 4086–4097, May 2023.

[19] Bolei Chen, Yongzheng Cui, Ping Zhong, Wang yang, Yixiong Liang, and Jianxin Wang, “STExplorer: A Hierarchical Autonomous Exploration Strategy with Spatio-Temporal Awareness for Aerial Robots,” ACM Transactions on Intelligent Systems and Technology, May 2023.

[20] Yixiong Liang, Zhihua Yin, Haotian Liu, Hailong Zeng, Jianxin Wang, Jianfeng Liu, and Nanying Che, “Weakly Supervised Deep Nuclei Segmentation with Sparsely Annotated Bounding Boxes for DNA Image Cytometry,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 20, no. 1, pp. 785–795, 2023.

[21] Qing Liu, Haotian Liu, Wei Ke, and Yixiong Liang, “Automated Lesion Segmentation in Fundus Images with Many-to-Many Reassembly of Features,” Pattern Recognition, vol. 136, p. 109191, 2023.

[22] Shichao Kan, Yixiong Liang, Min Li, Yigang Cen, Jianxin Wang, and Zhihai He, “Coded Residual Transform for Generalizable Deep Metric Learning,” in Advances in Neural Information Processing Systems (NeurIPS), 2022.

[23] Qing Liu, Haotian Liu, Yang Zhao, and Yixiong Liang, “Dual-Branch Network with Dual-Sampling Modulated Dice Loss for Hard Exudate Segmentation in Color Fundus Images,” IEEE Journal of Biomedical and Health Informatics, vol. 26, no. 3, pp. 1091–1102, 2022.

[24] Ping Zhong, Bolei Chen, Siyi Lu, Xiaoxi Meng, and Yixiong Liang, “Information-Driven Fast Marching Autonomous Exploration with Aerial Robots,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 810–817, 2022.

[25] Yongsheng Zhang, Qing Liu, Yang Zhao, and Yixiong Liang, “MEJIGCLU: More Effective Jigsaw Clustering For Unsupervised Visual Representation Learning,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, pp. 2135–2139.

[26] Ruixiang Geng, Qing Liu, Shuo Feng, and Yixiong Liang, “Learning Deep Pathological Features for WSI-Level Cervical Cancer Grading,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, pp. 1391–1395.

[27] Yao Xiang, Zhujun He, Qing Liu, Jialin Chen, and Yixiong Liang, “Autofocus of Whole Slide Imaging Based on Convolution and Recurrent Neural Networks,” Ultramicroscopy, vol. 220, p. 113146, 2021.

[28] Hulin Kuang, Yixiong Liang, Ning Liu, Jin Liu, and Jianxin Wang, “BEA-SegNet: body and edge aware network for medical image segmentation,” in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021, pp. 939–944. (Best Student Paper Award)

[29] Yixiong Liang, Changli Pan, Wanxin Sun, Qing Liu, and Yun Du, “Global Context-Aware Cervical Cell Detection with Soft Scale Anchor Matching,” Computer Methods and Programs in Biomedicine, p. 106061, 2021.

[30] Yixiong Liang, Zhihong Tang, Meng Yan, Jialin Chen, Qing Liu, and Yao Xiang, “Comparison Detector for Cervical Cell/Clumps Detection in the Limited Data Scenario,” Neurocomputing, vol. 437, pp. 195–205, 2021.

[31] Yao Xiang, Wanxin Sun, Changli Pan, Meng Yan, Zhihua Yin, and Yixiong Liang, “A Novel Automation-Assisted Cervical Cancer Reading Method Based on Convolutional Neural Network,” Biocybernetics and Biomedical Engineering, vol. 40, no. 2, pp. 611–623, 2020.

[32] Qing Liu, Beiji Zou, Yang Zhao, and Yixiong Liang, “A Deep Gradient Boosting Network for Optic Disc and Cup Segmentation,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp. 971–975.

[33] Meng Yan, Qing Liu, Zhihua Yin, Du Wang, and Yixiong Liang, “A Bidirectional Context Propagation Network for Urine Sediment Particle Detection in Microscopic Images,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp. 981–985.

[34] Yao Xiang, Jialin Chen, Qing Liu, and Yixiong Liang, “Disentangled Representation Learning Based Multidomain Stain Normalization For Histological Images,” in IEEE International Conference on Image Processing (ICIP), 2020, pp. 360–364.

[35] Yixiong Liang, Meng Yan, Zhihong Tang, Zhujun He, and Jianfeng Liu, “Learning to Autofocus Based on Gradient Boosting Machine for Optical Microscopy,” Optik, vol. 198, p. 163002, 2019.

[36] Yingjun Jiang, Jianxin Wang, Yixiong Liang, and Jiazhi Xia, “Combining Static and Dynamic Features for Real-Time Moving Pedestrian Detection,” Multimedia Tools and Applications, vol. 78, no. 3, pp. 3781–3795, 2019.

[37] Yixiong Liang, Yuan Mao, Jiazhi Xia, Yao Xiang, and Jianfeng Liu, “Scale-Invariant Structure Saliency Selection for Fast Image Fusion,” Neurocomputing, vol. 356, no. 9, pp. 119–130, 2019.

[38] Yixiong Liang, Yuan Mao, Zhihong Tang, Meng Yan, Yuqian Zhao, and Jianfeng Liu, “Efficient Misalignment-Robust Multi-Focus Microscopical Images Fusion,” Signal Processing, vol. 161, no. 8, pp. 111–123, 2019.