王立志 |
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副教授/特别研究员/博士生导师 |
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北京理工大学计算机学院 | |
可视媒体计算实验室 | |
办公室:中心教学楼815室 | |
Email:wanglizhi@bit.edu.cn | |
研究领域:计算摄像学,图像视频处理,视觉与图形学,智能多媒体 |
王立志,特别研究员,博士生导师。2011年和2016年获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联合培养项目,2013年至2016年于微软亚洲研究院实习。已经发表多篇国际顶级论文,包括TPAMI、IJCV、TIP等期刊和CVPR、ICCV等会议。荣获中国电子学会2018年度优秀博士学位论文奖,IEEE VCIP 2016最佳论文奖。
本人每年招收博士生1-2名、硕士生3-4名,额外与兼职教授共同招收硕士生2-3名,长期招收科研入门的本科生以及科研合作的博士后。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。团队会提供非常优越的工作环境、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,并开始研究和发表论文!
中国计算机学会多媒体专委会委员
中国图象图形学会多媒体专委会委员
TPAMI, IJCV, TIP, SIGGRAPH, CVPR, ICCV, IJCAI审稿人
《大数据驱动的类人智能感知与情感交互关键技术》,国家重点研发计划,子课题负责人
《编解码联合优化的计算光谱成像》,国家自然科学基金面上项目,项目负责人
《无人机智能视觉成像领域项目》,国防重点项目,项目负责人
[1] Hansen Feng, Lizhi Wang, Yuzhi Wang, Hua Huang, Learnability Enhancement for Low-light Raw Denoising: Where Paired Real Data Meets Noise Modeling, In ACM Multimedia (ACMMM), 2022. (CCF A 类)
[2] 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)
[3] 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.
[4] 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)
[5] Zhan Wang, Lizhi Wang, Hua Huang, Sparse additive discriminant canonical correlation analysis for multiple features fusion, Neurocomputing, 2021,
[6] 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)
[7] 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)
[8] Zhan Wang, Lizhi Wang, Jun Wan, Hua Huang, Shared low-rank correlation embedding for multiple feature fusion, IEEE Transactions on Multimedia (TMM), 2020.
[9] Zhan Wang, Lizhi Wang, and Hua Huang. Joint low rank embedded multiple features learning for audio-visual emotion recognition. Neurocomputing, 2020.
[10] Maoqing Zhang, Lizhi Wang, Lei Zhang, Hua Huang, High light efficiency snapshot spectral imaging via spatial multiplexing and spectral mixing, OSA Optics Express, 2020.
[11] Zhan Wang, Lizhi Wang, Hua Huang, Structure Preserving Multi-View Dimensionality Reduction, In IEEE International Conference on Multimedia and Expo (ICME), 2020.
[12] 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)
[13] 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)
[14] 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)
[15] 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)
[16] Tao Zhang, Ying Fu, Lizhi Wang, and Hua Huang. Hyperspectral image reconstruction using deep external and internal learning. In IEEE International Conference on Computer Vision (ICCV), 2019. (CCF A类)
[17] Maoqing Zhang, Lizhi Wang, Lei Zhang, and Hua Huang. Compressive hyperspectral imaging with non-zero mean noise. OSA Optics Express, 2019.
[18] 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.
[19] 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)
[20] 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)
[21] 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. (Oral, Best Paper Award)
[22] 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)
[23] Lizhi Wang, Zhiwei Xiong, Dahua Gao, Guangming Shi, and Feng Wu. Dual-camera design for coded aperture snapshot spectral imaging. OSA Applied Optics, 2015.
[24] Dong Liu, Lizhi Wang, Li Li, Zhiwei Xiong, Feng Wu, and Wenjun Zeng. Pseudo-sequence-based light field image compression. In IEEE International Conference on Multimedia & Expo Workshops (ICMEW), pages 1–4. 2016. (Light Field Compression Challenge Winner Award)