个人简历

工作经历\r
2018年11月至今清华大学深圳国际研究生院，教授\r
2011年11月~2018年10月清华大学深圳研究生院，副教授\r
2008年1月~2011年11月清华大学深圳研究生院，讲师\r
2005年10月~2008年1月，清华大学，博士后\r
2014年2月~2015年2月美国加州伯克利分校，访问学者\r
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学术兼职\r
国家自然科学基金委函评专家\r
深圳市科创委项目评审专家

研究领域

"立体视频是新一代信息获取、传播与显示的前沿核心技术，具有高沉浸感、宽视场等特点，相比平面视频，场景几何数据信息显著增长，面临着多项理论与技术挑战。"

近期论文

B. Zhang, Y. Guo, Y. Li, Y. He, HQ Wang, QH Dai, “Memory Recall: A Simple Neural Network Training Framework Against Catastrophic Forgetting”, IEEE Transactions on Neural Networks and Learning Systems (TNNSL, IF: 8.793), 2021. 通讯作者\r
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L.Song, HQ Wang, and Z. Wang, “BridgingtheGapbetween2Dand3DContextsinCTVolumeforLiverandTumorSegmentation”, IEEE Journal of Biomedical and Health Infortmatics (JBHI, IF: 5.772), 2021. 通讯作者\r
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HQ Wang, X. Hu, X. Zhao and Y. Zhang, “Wide Weighted Attention Multi-Scale Network for Accurate MR Image SuperResolution”, IEEE Trans on Circuits and Systems for Video Tech. (TCSVT, IF:4.133), doi:10.1109/TCSVT.2021.3070489. 2021. 通讯作者\r
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Li X，Zhang G，Wu J, Zhang Y, Zhao Z, Lin X, Qiao H, Xie H, Wang HQ, Fang L, Dai Q, Reinforcing neuron extraction and spike inference in calcium imaging using deep self-supervised learning, Nature Methods (IF: 30.8), 2021 通讯作者\r
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H. Wang, Z. Li and HQ Wang, “Few-Shot Steel Surface Defect Detection,” IEEE Transactions on Instrumentation and Measurement (TIM, IF: 4.016), 2021. 通讯作者\r
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X. Li, G. Zhang, H. Qiao, B. Feng, Y. Deng, J. Wu, Y. He, J. Yun, X. Lin, H. Xie, Wang HQ*, Q. Dai. Unsupervised content-preserving transformation for optical microscopy, Light: Science & Applications(IF: 13.7), 2021. 通讯作者\r
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Y. Zhang, Y. Feng, X. Liu, D. Zhai, X. Ji, HQ. Wang, and Q. Dai, “Color-Guided Depth Image Recovery with Adaptive Data Fidelity and Transferred Graph Laplacian Regularization”, IEEE Trans. on Circuits and Systems for Video Technology(TCSVT, IF: 4.133), DOI 10.1109/TCSVT. 2018.2890574, 2020. 通讯作者\r
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Wang HQ* , Y. Luo, W. An, Q. Sun, J. Xu, and L. Zhang. PID Controller-Based Stochastic Optimization Acceleration for Deep Neural Networks, IEEE Transactions on Neural Networks and Learning Systems (TNNSL, IF: 8.793), 2020. 通讯作者\r
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Song L, Lin JZ, Wang Jane, Peng YB, Zhang YB, Wang HQ*. An End-to-end Multi-task Deep Learning Framework for Skin Lesion Analysis, IEEE Journal of B iomedical and Health Infortmatics (JBHI, IF: 5.772), 2020. 通讯作者.\r
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J. Xu, Y. Hou, D. Ren, L. Liu, F. Zhu, M. Yu , Wang HQ*, and L. Shao, STAR: A Structure and Texture Aware Retinex Model, IEEE Transactions on Image Processing (TIP, IF: 9.34), Vol. 29, p. 5022-5037, 2020.通讯作者\r
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X. Hu, R. Ma, Z. Liu, Y. Cai, X. Zhao, Y. Zhang, Wang HQ, Pseudo 3D Auto Correlation Network for Real Image Denoising, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2021. CCF A类会议, 通讯作者\r
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Yuanhao Cai , Xiaowan Hu, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Donglai Wei, Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training, NeurIPs, 2021. CCF A类会议, 通讯作者\r
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Xiaowan Hu ,YuanhaoCai, ZhihongLiu1, HaoqianWang, and Yulun Zhang, Multi-Scale Selective Feedback Network with Dual Loss for Real Image Denoising, International Joint Conference on Artificial Intelligence (IJCAI), 2021. CCF A类会议, 通讯作者\r
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Y. Cai, Z. Wang, Z. Luo, B. Yin, A. Du, HQ Wang, X. Zhang, X. Zhou, E. Zhou, and J. Sun, Learning Delicate Local Representations for Multi-Person Pose Estimation, ECCV, 2019\r
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W. An, H. Wang, Q. Sun, J. Xu, Q. Dai, L. Zhang, “A pid controller approach for stochastic optimization of deep networks”, Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) . 2018: 8522-8531.