数学
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朱聪聪
博士后
朱聪聪，博士后研究员。2015年和2022年分别在苏州大学文正学院和上海大学取得学士和博士学位。2022年-2023年在扬州大学信息工程学院担任讲师。
朱聪聪博士于2023年2月加入中国科学技术大学苏州高等研究院。近三年第一作者发表论文 10 篇, 主要发表在 CVPR (Oral), ICCV, AAAI, ACM MM, IEEE Trans. Multimedia 以及 Pattern Recognition 等顶级刊物上，并担任CVPR、IJCV、Pattern Recognition、ICAPSS、Neurocomputing 及 ICME 审稿人。
电子邮箱：cczly@ustc.edu.cn
联系地址：中国科学技术大学苏州高等研究院亲民楼216
主要研究方向
复杂环境下的人脸视觉分析，视频理解与分析，自监督学习及对抗学习，三维结构重建。
获奖及荣誉
2020-2021 ：国家奖学金，上海大学优秀学生，校长奖学金提名
2021-2022 ：上海市优秀毕业生，国家奖学金，上海大学“学术启明星”，上海大学优秀学生，上海市计算机学会优秀博士学位论文提名
学术论文及著作
1. Zhu C, Wan X, Li J, et al. Occlusion-robust Face Alignment using A Viewpoint-invariant Hierarchical Network Architecture[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022： Accepted. (CCF-A, 被推选为前 4% Oral presentation，Google Scholar Top Publications: No.4)
2. Zhu C, Li X, Li J, et al. Improving Robustness of Facial Landmark Detection by Defending Against Adversarial Attacks[C]//Proceedings of the IEEE/CVF International Conference on Computer Vision. 2021: 11751-11760. (CCF-A， Google Scholar Top Publications：No.17)
3. Zhu C, Liu H, Yu Z, et al. Towards omni-supervised face alignment for large scale unlabeled videos[C]//Proceedings of the AAAI Conference on Artificial Intelligence. 2020, 34(07): 13090-13097. (CCF-A, Spotlight paper, Google Scholar Top Publications：No.44)
4. Zhu C, Li X, Li J, et al. Spatial-temporal knowledge integration: robust self-supervised facial landmark tracking[C]//Proceedings of the 28th ACM International Conference on Multimedia. 2020: 4135-4143. (CCF-A)
5. Zhu C, Li X, Li J, et al. Multi-sourced Knowledge Integration for Robust Self-Supervised Facial Landmark Tracking[ j]. IEEE Transactions on Multimedia, 2022, In Press, doi: 10.1109/TMM.2022.3212265. (中科院升级版一区 top，CCF-B, IF=8.1)
6. Zhu C, Li X, Li J, et al. Reasoning structural relation for occlusion-robust facial landmark localization[J]. Pattern Recognition, 2022, 122: 108325. (中科院升级版一区 top，CCF-B, IF=8.5)
7. Zhu C, Wu S, Yu Z, et al. Multi-agent deep collaboration learning for face alignment under different perspectives[C]//2019 IEEE International Conference on Image Processing. IEEE, 2019: 1785-1789. (CCF-C)
8. Zhu C, Wang X, Wu S, et al. Learning Relational-Structural Networks for Robust Face Alignment[C]//International Conference on Artificial Neural Networks. Springer, Cham, 2019: 306-316. (CCF-C)
9. Zhang J*, Zhu C*, Wu S, et al. Learning Deformable Hourglass Networks (DHGN) for Unconstrained Face Alignment[C]//2019 IEEE International Conference on Image Processing. IEEE, 2019: 1960-1964. (CCF-C,*共一作)
10. Zhu C, Yu Z, W S, Hao L. Dual-Cycle Deep Reinforcement Learning for Stabilizing Face Tracking[C]//2019 IEEE International Conference on Multimedia & Expo Workshops (ICME Workshop). IEEE, 2019: 543-548. (EI)
