目录
硕士报考志愿采集    更新日期:2021年8月28日
姓 名 谢晋 性 别
出生年月 1981年3月 籍贯 湖北
民 族 汉族 政治面貌 党员
最后学历 博士研究生 最后学位 工学博士
技术职称 教授 导师类别 博士生导师
导师类型 校内 兼职导师
行政职务 Email csjxie@njust.edu.cn
工作单位 高维信息智能感知与系统教育部重点实验室 邮政编码
通讯地址 南京理工大学计算机学院
单位电话
个人主页 https://csjinxie.github.io/
指导学科
学科专业(主) 0812|计算机科学与技术 招生类别 博、硕士 所在学院 计算机科学与工程学院
研究方向

计算机视觉、机器学习、机器人控制

工作经历

青年教授     南京理工大学计算机科学与工程学院             2017.9-

研究员         纽约大学阿布扎比分校,纽约大学Tandon工学院电子工程系    2017.1-2017.8

博士后         纽约大学阿布扎比分校,纽约大学Tandon工学院电子工程系    2014.2-2016.12

研究助理     中科院深圳先进技术研究院                            2012. 11-2014.1

 

教育经历

博士             香港理工大学计算机系生物特征识别中心          2008.3-2012.10

硕士             西北工业大学自动化学院                                 2004.9-2007.7

本科             沈阳航空工业学院自动化系                             2000.9-2004.7

获奖、荣誉称号

2017年入选江苏特聘教授,2018年入选国家四青人才

社会、学会及学术兼职

国际会议高级程序委员会 (Senior Program Committee, SPC) 成员:AAAI Conference on Artificial Intelligence (AAAI), International Joint Conference on Artificial Intelligence (IJCAI).

国际会议专刊主席 (Special Issue Chair):Asian Conference on Pattern Recognition 2017.

国际期刊审稿人:IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Cybernetics, Pattern Recognition, Pattern Recognition Letters, Image and Vision Computing.

国际会议程序委员会成员:IEEE Conference on Computer Vision and Pattern Recognition (CVPR), International Conference on Computer Vision (ICCV),  European Conference on Computer Vision (ECCV).

国际期刊客座编辑:Pattern Recognition.

科研项目

三维几何深度学习及在三维场景理解中的应用,国家级青年人才项目,2019.1-2021.12

基于深度学习的三维物体特征表示,江苏特聘教授资助项目,2017.9-2020.8

基于结构化循环一致性的三维形状局部特征表示及匹配,国家自然基金面上项目,2019.1-2022.12

多模态融合的道路可通行区域检测,上汽基金会项目,2019.9-2021.3

发表论文

会议

1. Le Hui, Jia Yuan, Mingmei Cheng, Jin Xie, Xiaoya Zhang and Jian Yang, Superpoint Network for Point Cloud Oversegmetation, International Conference on Comupter Vision, ICCV 2021.

2. Le Hui, Hang Yang, Mingmei Cheng, Jin Xie and Jian Yang, Pyramid Point Cloud Transformer for Large-scale Place Recognition, International Conference on Comupter Vision, ICCV 2021.

3. Haobo Jiang, Yaqi Shen, Jin Xie, Jun Li, Jianjun Qian and Jian Yang, Sampling Network Guided Cross-entropy Method for Unsupervised Point Cloud Registration, International Conference on Comupter Vision, ICCV 2021.

4. Yifan Zhao, Le Hui and Jin Xie, SSPU-Net: Self-Supervised Point Cloud Upsampling via Differentiable Rendering, ACM Conference on Multimedia, ACM MM 2021.

5. Haobo Jiang, Jin Xie, Jianjun Qian and Jian Yang, Planning with Learned Dynamic Model for Unsupervised Point Cloud Registration, International Joint Conference on Artificial Intelligence, IJCAI 2021.

6. Haobo Jiang, Jin Xie and Jian Yang, Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks, AAAI Conference on Artificial Intelligence, AAAI 2021.

7. Mingmei Cheng, Le Hui, Jin Xie and Jian Yang, SSPC-Net: Semi-supervised Semantic 3D Point Cloud Segmentation Network, AAAI Conference on Artificial Intelligence, AAAI 2021.

8. Le Hui, Rui Xu, Jin Xie, Jianjun Qian and Jian Yang, Progressive Point Cloud Deconvolution Generation Network, European Conference on Computer Vision, ECCV 2020.

9. Mingmei Cheng, Le Hui, Jin Xie, Jian Yang and Hui Kong, Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation, IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020.

10. Kangkan Wang, Jin Xie, Guofeng Zhang, Lei Liu and Jian Yang, Sequential 3D Human Pose and Shape Estimation From Point Clouds, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2020.

11. Guoxian Dai,Jin Xie and Yi Fang, Siamese CNN-BiLSTM architecture for 3D shape representation learning,International Joint Conference on Artificial IntelligenceIJCAI 2018.

12. Jing Zhu,Jin Xie and Yi Fang, Learning adversarial 3D model generation with 2D image enhancer,AAAI Conference on Artificial Intelligence 2018AAAI 2018.

13. Guoxian Dai,Jin Xie and Yi Fang, Metric-based generative adversarial network,ACM Conference on MultimediaACM MM 2017.

14. Jin Xie, Guoxian Dai, Fan Zhu and Yi Fang, Learning Barycentric representations of 3D shapes for sketch-based 3D shape retrieval, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017.

15. Jin Xie, Meng Wang and Yi Fang, Learned binary spectral shape descriptor for 3D shape correspondence, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016.

16. Jin Xie, Yi Fang, Fan Zhu and Edward K.Wong, Deepshape:deep learned shape descriptor for 3D shape matching and retrieval, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015.

17. Jin Xie, Fan Zhu, Guoxian Dai and Yi Fang, Progressive shape-distribution-encoder for 3D shape retrieval, ACM Conference on Multimedia,ACM MM 2015.

18. Yi Fang, Jin Xie, Guoxian Dai, Meng Wang, Fan Zhu, Tiantian Xu and Edward Wong, 3D deep shape descriptor, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015.

19. Guoxian Dai, Jin Xie, Fan Zhu and Yi Fang, Deep correlation learning for sketch based 3D shape retrieval, AAAI Conference on Artificial Intelligence, AAAI 2017.

20. Fan Zhu, Jin Xie and Yi Fang, Heat diffusion long-short term memory learning for 3D shape analysis, European Conference on Computer Vision, ECCV 2016.

21. Fan Zhu, Jin Xie and Yi Fang, Learning cross-domain neural networks for sketch-based 3D shape retrieval, AAAI Conference on Artificial Intelligence, AAAI 2016.

期刊

1. Jin Xie, Guoxian Dai, Fan Zhu, Edward K.Wong and Yi Fang, Deepshape:deep-learned shape descriptor for 3D shape retrieval, IEEE Trans. Pattern  Analysis and Machine Intelligence, 2017.

2. Jin Xie, Guoxian Dai and Yi Fang, Deep multi-metric learning for shape-based 3D model retrieval, IEEE Trans. Multimedia, 2017.

3. Jin Xie, Guoxian Dai, Fan Zhu, Ling Shao and Yi Fang, Deep non-linear metric learning for 3D shape retrieval, IEEE Trans. Cybernetics, 2018.

4. Jin Xie, Fan Zhu, Guoxian Dai, Ling Shao and Yi Fang, Progressive shape-distribution-encoder, IEEE Trans. Image Processing, 2017.

5. Jin Xie, Lei Zhang, Jane You and Simon Shiu, Effective texture classification by texton encoding induced statistical features, Pattern Recognition, 2015.

6. Jianquan Yang#, Jin Xie#, Guopu Zhu, and Yunqing Shi, An effective method for detecting double JPEG compression with the same quantization matrix, IEEE Trans. Information Forensics and Security, 2014 (#: Equal contribution).

7. Jin Xie and Yi Fang, Dynamic texture recognition with video set based collaborative representation, Image and Vision Computing, 2016.

9. Guoxian Dai, Jin Xie and Yi Fang, Deep correlated holistic metric learning for sketch-based 3D shape retrieval, IEEE Trans. Image Processing, 2018.

10. Fan Zhu, Ling Shao, Jin Xie and Yi Fang, From handcrafted to learned representations for human action recognition: a survey, Image and Vision Computing, 2016

教学活动

深度学习,南京理工大学,2020, 2021.

传感器原理,南京理工大学, 2020.

Capstone Projects,  纽约大学阿布扎比分校, 2015, 2016.

图像处理, 香港理工大学, 2010.

Java 编程, 香港理工大学, 2008.

小波信号处理, 西北工业大学,  2006.

指导学生情况

欢迎对机器学习、计算机视觉和机器人感兴趣的同学报考本人的硕士、博士研究生。

现指导博士生六名、硕士生七名。

曾指导纽约大学Tandon工学院博士生三名。

我的团队

更多信息请参考个人主页,https://csjinxie.github.io/.