教育经历：

2015-09至2020-06   清华大学       信息与通信工程    博士

2011-09至2015-06   华南理工大学     信息工程       学士

工作经历：

2023-07至今      中国科学院自动化研究所多模态人工智能系统全国重点实验室  副研究员

2022-07至2023-07  中国科学院自动化研究所多模态人工智能系统全国重点实验室  助理研究员

2020-07至2022-07  中国科学院自动化研究所模式识别国家重点实验室         博士后

发表论文：

[1] J. Wang, C. Yuan, B. Li, Y. Deng, W. Hu and S. Maybank, Self-Prior Guided Pixel Adversarial Networks for Blind Image Inpainting, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.

[2] J. Wang, Z. Chen, C. Yuan, B. Li, W. Ma, W. Hu, Hierarchical Curriculum Learning for No-reference Image Quality Assessment, International Journal of Computer Vision (IJCV), 2023.

[3] Z. Wang, J. Wang, N. Ge and J. Lu, HiMoReNet: A Hierarchical Model for Human Motion Refinement, IEEE Signal Processing Letters, 2023.

[4] H. Qin, L. Han, W. Xiong, J. Wang, W. Ma, B. Li, W. Hu; Learning to Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 22314-22323, 2023

[5] H. Qin, L. Han, J. Wang, B. Li, et al., Attention-aware Learning for Hyperparameters Prediction in Image Processing Pipelines, European Conference on Computer Vision (ECCV), pp. 271—287, 2022.

[6] Z. Chen, J. Wang, B. Li, C. Yuan, W. Xiong, R. Cheng, W. Hu, Teacher-Guided Learning for Blind Image Quality Assessment, Asian Conference on Computer Vision (ACCV), 2022.

[7] K. Zhang, M. Li, H Liang, J. Wang, F. Yang, S. Xu, A. Abubakar. Deep feature-domain matching for cardiac-related component separation from a chest electrical impedance tomography image series: proof-of-concept study. Physiol Meas. vol. 43, no. 12, 2022.

[8] J. Wang; Y. Duan; X. Tao*; M. Xu; J. Lu; Semantic Perceptual Image Compression with a Laplacian Pyramid of Convolutional Networks, IEEE Transactions on Image Processing (TIP), vol. 30, pp. 4225-4237, 2021.

[9] J. Wang; X. Tao*; M. Xu; Y. Duan; J. Lu; Hierarchical Objectness Network for Region Proposal Generation and Object Detection, Pattern Recognition, vol. 83, pp. 260-272, 2018. 

[10] J. Wang, Y. Duan, X. Tao and J. Lu, Local-to-Global Semantic Supervised Learning for Image Captioning, IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020, pp. 1-6.

[11] J. Wang, X. Tao, M. Xu, J. Lu, Semantic Perceptual Image Compression with a Laplacian Pyramid of Convolutional Networks, IEEE International Conference on Image Processing (ICIP) , pp. 699-703, 2019.  

[12] J. Wang, X. Tao, M. Xu, J. Lu, Boundary Objectness Network for Object Detection and Localization, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2336-2340, 2018.  

[13] J. Wang, X. Tao, C. Jiang, S. Li, J. Lu, A nonparametric Bayesian method of structural saliency dictionary learning for image compression, IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 1200-1204, 2017.

[14] X. Tao, S. li, Z. Zhang, X. Liu, J. Wang, and J. Lu, “Prior-information-based remote sensing image compression with bayesian dictionary learning,” IEEE Vehicular Technology Conference (VTC), 2017.

[15] J. Wang, X. Tao, X. Liu,et al., Quantization and Entropy Coding Scheme for Dictionary Learning Based Image Compression, IEEE Vehicular Technology Conference (VTC), pp. 1-5, 2016.