基本信息

• 职称：教授（硕士生导师、博士生导师）

• 研究方向：图像视频处理、计算摄像学、计算机视觉、智能媒体计算

• 电子邮箱： wanglizhi@bnu.edu.cn

个人简介

王立志，教授、博士生导师、国家优青。2011年和2016年在西安电子科技大学获得工学学士和工学博士学位，博士期间入选微软亚洲研究院（MSRA）联合培养项目，于2013年至2016年在微软亚洲研究院实习。主持多项国家级项目，包括国家优秀青年科学基金项目、应用创新装备预研项目、国家自然科学基金面上项目，主持多项企业委托项目，包括华为、OPPO、兵科院、航天五院。发表论文50余篇，包括TPAMI、IJCV、TIP等CCF A类期刊和CVPR、ICCV、MM等CCF A类会议，担任IEEE TIP编委（Associate Editor）。荣获CCF A类会议ACM MM 2022最佳论文提名奖、中国电子学会2018年度优秀博士学位论文奖、IEEE VCIP 2016最佳论文奖、北京市优秀本科毕业设计指导教师。

教育背景

• 2011年—2016年 西安电子科技大学-微软亚洲研究院 智能信息处理 博士 导师：石光明教授，吴枫教授

• 2007年—2011年 西安电子科技大学大学电子信息工程学院，探测制导与控制技术，学士

工作经历

• 2024年07月-至今 北京师范大学-人工智能学院 教授

• 2023年08月-2024年07月 北京理工大学-计算机学院 教授

• 2018年12月-2023年08月 北京理工大学-计算机学院 副教授

• 2017年01月-2018年12月 北京理工大学-计算机学院 博士后

主持和参加的科研项目

• 国家优秀青年科学基金项目

• 国家自然科学基金面上项目

• 国家自然科学基金青年项目

• 应用创新装备预研项目

• 国家重点研发计划子课题

• 北京市科技计划项目

主要学术成果

1. Tong Li, Hansen Feng, Lizhi Wang*, Lin Zhu, Zhiwei Xiong, Hua Huang, Stimulating the Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024. (CCF A类)

2. Lizhi Wang, Lingen Li, Weitao Song, Lei Zhang, Zhiwei Xiong, Hua Huang, Non-serial Quantization-aware Deep Optics for Snapshot Hyperspectral Imaging, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024. (CCF A类)

3. Xin Wang, Lizhi Wang*, Xiangtian Ma, Maoqing Zhang, Lin Zhu, Hua Huang, In2SET: Intra-Inter Similarity Exploiting Transformer for Dual-Camera Compressive Hyperspectral Imaging, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. (CCF A类)

4. Hansen Feng, Lizhi Wang*, Yuzhi Wang, Haoqiang Fan, Hua Huang, Learnability Enhancement for Low-Light Raw Image Denoising: A Data Perspective, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023. (CCF A类)

5. Jie Lian, Lizhi Wang*, He Sun, Hua Huang, GT-HAD: Gated Transformer for Hyperspectral Anomaly Detection, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.

6. Hongyuan Wang, Lizhi Wang*, Chang Chen, Xue Hu, Fenglong Song, Hua Huang, Learning Spectral-wise Correlation for Spectral Super-Resolution: Where Similarity Meets Particularity, ACM MM, 2023. (CCF A类)

7. Lingen Li, Lizhi Wang*, Weitao Song, Lei Zhang, Zhiwei Xiong, Hua Huang, Quantization-Aware Deep Optics for Diffractive Snapshot Hyperspectral Imaging, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. (CCF A类)

8. Hansen Feng, Lizhi Wang*, Yuzhi Wang, Hua Huang, Learnability enhancement for low-light raw denoising: Where paired real data meets noise modeling, ACM MM,2022. (CCF A类) (Best Paper Runner-Up Award)

9. Lingfei Song, Lizhi Wang*, Min H. Kim, Hua Huang, High-Accuracy Image Formation Model for Coded Aperture Snapshot Spectral Imaging, IEEE Transactions on Computational Imaging (TCI), 2022.

10. Lizhi Wang, Shipeng Zhang, Hua Huang, Adaptive Dimension-discriminative Low-rank Tensor Recovery for Computational Hyperspectral Imaging, International Journal of Computer Vision (IJCV), 2021. (CCF A类)

11. Zhan Wang, Lizhi Wang*, Hua Huang, Sparse additive discriminant canonical correlation analysis for multiple features fusion, Neurocomputing, 2021

12. Shipeng Zhang, Lizhi Wang*, Lei Zhang, Hua Huang, Learning Tensor Low-Rank Prior for Hyperspectral Image Reconstruction, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (CCF A类)

13. Lizhi Wang, Chen Sun, Maoqing Zhang, Ying Fu, and Hua Huang. DNU: Deep non-local unrolling for computational spectral imaging. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (CCF A类)

14. Zhan Wang, Lizhi Wang*, Jun Wan, Hua Huang, Shared low-rank correlation embedding for multiple feature fusion, IEEE Transactions on Multimedia (TMM), 2020.

15. Zhan Wang, Lizhi Wang*, and Hua Huang. Joint low rank embedded multiple features learning for audio-visual emotion recognition. Neurocomputing, 2020.

16. Zhan Wang, Lizhi Wang*, Hua Huang, Structure Preserving Multi-View Dimensionality Reduction, In IEEE International Conference on Multimedia and Expo (ICME), 2020.

17. Lizhi Wang, Zhiwei Xiong, Hua Huang, Guangming Shi, Feng Wu, and Wenjun Zeng. High-speed hyperspectral video acquisition by combining nyquist and compressive sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019. (CCF A类)

18. Lizhi Wang, Tao Zhang, Ying Fu, and Hua Huang. HyperReconNet: Joint coded aperture optimization and image reconstruction for compressive hyperspectral imaging. IEEE Transactions on Image Processing (TIP), 2019. (CCF A类)

19. Lizhi Wang, Chen Sun, Ying Fu, Min H Kim, and Hua Huang. Hyperspectral image reconstruction using a deep spatial-spectral prior. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. (CCF A类)

20. Shipeng Zhang, Lizhi Wang*, Ying Fu, Xiaoming Zhong, and Hua Huang. Computational hyperspectral imaging based on dimension-discriminative low-rank tensor recovery. In IEEE International Conference on Computer Vision (ICCV), 2019. (CCF A类)

21. Lizhi Wang, Zhiwei Xiong, Guangming Shi, Wenjun Zeng, and Feng Wu. Simultaneous depth and spectral imaging with a cross modal stereo system. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2018.

22. Lizhi Wang, Zhiwei Xiong, Guangming Shi, Feng Wu, and Wenjun Zeng. Adaptive nonlocal sparse representation for dual-camera compressive hyperspectral imaging. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017. (CCF A类)

23. Zhiwei Xiong, Lizhi Wang, Huiqun Li, Dong Liu, and Feng Wu. Snapshot hyperspectral light field imaging. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (CCF A类)

24. Lizhi Wang, Zhiwei Xiong, Guangming Shi, Wenjun Zeng, and Feng Wu. Compressive hyperspectral imaging with complementary RGB measurements. In Visual Communications and Image Processing (VCIP), 2016. (Best Paper Award)

25. Lizhi Wang, Zhiwei Xiong, Dahua Gao, Guangming Shi, Wenjun Zeng, and Feng Wu. High-speed hyperspectral video acquisition with a dual-camera architecture. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. (CCF A类)

奖励与荣誉

• CCF A类会议ACM MM 2022最佳论文提名奖（通讯作者）

• 中国电子学会2018年度优秀博士学位论文奖

• IEEE VCIP 2016最佳论文奖（第一作者）

• 北京市优秀本科毕业设计指导教师。

• IEEE ICASSP 2024 光谱视觉挑战赛冠军

学术与社会服务

• 中国计算机学会多媒体技术专委会委员

• 中国图象图形学会多媒体专委会委员

• IEEE TIP编委 (Associate Editor)

• TPAMI, IJCV, TIP, SIGGRAPH, CVPR, ICCV, IJCAI等刊物审稿人

招生说明

本人每年招收博士生1名、硕士生2-3名，长期招收科研入门的本科生，以及有志于教师岗位的博士后。本人会亲自指导每一位学生，团队的其他老师和高年级同学也会提供指导。团队会提供优越的工作环境、计算资源、科研补助和国内外交流机会。请有兴趣加入团队的同学尽早联系，早日确定意向。详细招生理念请转阅团队主页https://vmcl.bnu.edu.cn/