肖国宝，博士毕业于厦门大学计算机科学与技术，2016-2018 厦门大学 航空航天学院 博士后，IEEE 高级会员，TIP/TMM/TCSVT等国际期刊审稿人，CVPR/ICCV/ECCV/AAAI等国际会议审稿人。

课程

Python程序设计、机器学习与模式识别、人工智能导论

在研项目

1. 国家自然科学基金面上项目“基于深度拓扑学习的高精准图像特征匹配方法研究”，时间：2025.01-2028.12，主持

2. 国家自然科学基金面上项目“基于多视图空间一致性的鲁棒模型拟合理论研究及应用”，时间：2021.01-2024.12，主持

3. 国家自然科学基金青年项目“新型确定性模型拟合方法研究及其应用”，时间：2018.01-2020.12，主持

4. 中国博士后第62批基金面上项目一等资助“基于超图的模型拟合方法研究及其在运动分割中的应用”，时间：2017.08-2018.07，主持

学术成果及荣誉

主要专注于计算机视觉、机器学习和大模型应用等方面的基础与应用研究，第一/通讯作者在TPAMI, IJCV, TIP, ICCV,ECCV, AAAI等国际高水平学术期刊/会议上发表学术论文50余篇，其中SCI一区和CCF A类期刊/会议30余篇。拥有国家发明专利11项，科研成果成功转化9项，出版《科学出版社》专著一部。

曾获得中国图象图形学学会“优秀博士学位论文”（全国10人）、福建省“优秀博士学位论文”、福建五四青年奖章、福州市青年科技奖等。

部分成果如下：

1. Guobao Xiao, Jun Yu，Jiayi Ma，Deng-Ping Fan and Ling Shao, Latent Semantic Consensus For Deterministic Geometric Model Fitting，IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024, 46 (9), 6139 - 6153 (SCI/JCR-1,TOP期刊, CCF A, IF=20.8)

2. Guobao Xiao, Xin Liu, Zhen Zhong, Xiaoqin Zhang, Jiayi Ma and Haibin Ling,T-Net++: Effective Permutation-Equivariance Network for Two-View Correspondence Pruning，IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024,1-17 (SCI/JCR-1, TOP期刊, CCF A, IF=20.8)

3. Hanzi Wang#, Guobao Xiao#(Equal Contribution), Yan Yan and David Suter, Searching for representative modes on hypergraphs for robust geometric model fitting, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019, 41(3), 687-711(SCI/JCR-1, TOP期刊, CCF A, IF=20.8)

4. Guobao Xiao, Hanzi Wang*, Yan Yanand David Suter, Superpixel-guided two-view deterministic geometric model fitting, International Journal of Computer Vision (IJCV), 2019, 127 (4), 323-339 (SCI/JCR-2, TOP期刊, CCF A, IF=11.6)

5. Guobao Xiao, Hanzi Wang*, Jiayi Ma and David Suter, Segmentation by Continuous Latent Semantic Analysis for Multi-structure Model Fitting, International Journal of Computer Vision (IJCV), 2021, 129,2034-2056 (SCI/JCR-2, TOP期刊, CCF A, IF=11.6)

6. Guobao Xiao, Jiayi Ma*, Shiping Wang and Changwen Chen, Deterministic Model Fitting by Local-NeighborPreservation and Global-Residual Optimization, IEEE Transactions on Image Processing (TIP), 2020, 29, 8988-9001 (SCI/JCR-1, TOP期刊, CCF A, IF=10.8)

7.  Linxin Zheng, GuobaoXiao*, Ziwei Shi, Shiping Wang and Jiayi Ma,MSA-Net: Establishing Reliable Correspondences by Multi-Scale Attention Network, IEEE Transactions on Image Processing (TIP), 2022, 31, 4598-4602 (SCI/JCR-1, TOP期刊, CCF A, IF=10.8)

8. Xin Liu, Guobao Xiao*, Riqing Chen*and Jiayi Ma, PGFNet: Preference-Guided Filtering Network for Two-View Correspondence Learning, IEEE Transactions on Image Processing (TIP), 2023, 32,1367-1378 (SCI/JCR-1, TOP, CCF A, IF=10.8)

9. Shunxing Chen, Guobao Xiao*, Junwen Guo, Qiangqiang Wu and Jiayi Ma, DHM-Net: Deep Hypergraph Modeling for Robust Feature Matching, IEEE Transactions on Image Processing (TIP),  2024 (SCI/JCR-1,TOP, CCF A, IF=10.8)

10. Junwen Guo, GuobaoXiao*, Shiping Wang and Jun Yu, Graph Context Transformation Learning for Progressive Correspondence Pruning, Thirty-EighthAAAI Conference on Artificial Intelligence (AAAI), 2024 (CCF A类会议)

11. Xiangyang Miao, GuobaoXiao*, Shiping Wang and Jun Yu, Graph Context Transformation Learning for Progressive Correspondence Pruning, Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024 (CCF A类会议)

12. Tangfei Liao, Xiaoqin Zhang*, Li Zhao, Tao Wang and Guobao Xiao*, Graph Context Transformation Learning for Progressive Correspondence Pruning, Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024 (CCF A类会议)

13. Zhen Zhong, Guobao Xiao*, Linxin Zheng, Yan Lu and Jiayi Ma, T-Net: Effective Permutation-Equivariant Network for Two-View Correspondence Learning, IEEE International Conference on Computer Vision (ICCV), 2021,1950-1959 (CCF A类会议)

14. Hanzi Wang, Guobao Xiao(Equal Contribution), Yan Yan, David Suter, Mode-seeking on hypergraphs for robust geometric model fitting, International Conference on Computer Vision (ICCV), 2015, 2902-2910 (CCF A类会议)

15. Zhenni Yu, Xiaoqin Zhang*, Li Zhao, Yi Bin and Guobao Xiao*, Exploring Deeper! Segment Anything Model with Depth Perceptionfor Camouflaged Object Detection, Proceedings of the 32nd ACM International Conference on Multimedia (MM), 2024, 4322--4330, (CCF A类会议)

欢迎有志于计算机视觉、机器学习、大模型领域的优秀硕士与博士研究生加入我们的团队，共同探索和创新！

注：本团队对学生要求较为严格，要求有丰富的深度学习编程基础和(博士生)要求发表SCI一区/CCF A 会议等科研基础！

https://guobaoxiao.github.io/