Shenghua Gao, Associate Professor


Shenghua Gao, Associate Professor 

Tel:  (021) 20685094
Email: gaoshh@@shanghaitech.edu.cn
Office: Room 1A-304C, SIST Building
Major: CS
Website: https://svip-lab.github.io/news.html
Shenghua Gao Research Group Recruitment (Click Here)

RESEARCH INTERESTS

Computer vision and Machine Learning


BIOGRAPHY

Shenghua Gao is an associate professor at ShanghaiTech University, China. He received the B.E. degree from the University of Science and Technology of China in 2008, and received the Ph.D. degree from the Nanyang Technological University in 2012. From Jun 2012 to Aug 2014, he worked as a research scientist in UIUC Advanced Digital Sciences Center in Prof Yi Ma's group, Singapore. From Jan 2015 to June 2015, he visited UC Berkeley as a visiting professor, hosted by Prof Jitendra Malik. His research interests include computer vision and machine learning. He has published more than 50 papers on image and video understanding in many top-tier international conferences and journals. He also served as a chair for some workshops in CVPR2017, ACCV2014, ACCV2016, and area chair in ICCV2019. He also served as the Associate Editor for IEEE Transactions on Circuits and Systems for Video Technology (IF:3.558) and Neurocomputing (IF:3.224). His work on personalized saliency detection was nominated as outstanding student award (runner-up) in IJCAI 2017. He was awarded the Microsoft Research Fellowship in 2010, and ACM Shanghai Young Research Scientist in 2015.


SELECTED PUBLICATIONS

1.Huang, Siyu.,Li, Xi.,Zhang, Zhongfei.,Wu, Fei.,Gao, Shenghua.,...and Han, Junwei.(2018).Body Structure Aware Deep Crowd Counting.IEEE TRANSACTIONS ON IMAGE PROCESSING,27(3),1049-1059.

2.Dongze Lian.,Lina Hu.,Weixin Luo.,Yanyu Xu.,Lixin Duan.,...and Shenghua Gao.(2018).Multiview Multitask Gaze Estimation With Deep Convolutional Neural Networks.IEEE Transactions on Neural Networksand Learning Systems,PP(99).

3.Wang, Z., Tang, X., Luo, W., and Gao, S. (2018). Face Aging With Identity-Preserved Conditional Generative Adversarial Networks. In Proceedings of the IEEE Conference on Computer Visionand Pattern Recognition (pp. 7939-7947).

4.Wang, Z., Tang, X., Luo, W., and Gao, S. (2018). Face Aging With Identity-Preserved Conditional Generative Adversarial Networks. In Proceedings of the IEEE Conference on Computer Visionand Pattern Recognition (pp. 7939-7947).

5.Liansheng Zhuang, Zihan Zhou, Shenghua Gao, Jingwen Yin, Zhouchen Lin, Yi Ma: Label Information Guided Graph Construction for Semi-Supervised Learning. IEEE Trans. Image Processing 26(9): 4182-4192, 2017.

6.Hao Zhu, Shenghua Gao: Locality Constrained Deep Supervised Hashing for Image Retrieval. IJCAI 2017: 3567-3573

7.Yanyu Xu, Nianyi Li, Junru Wu, Jingyi Yu, Shenghua Gao: Beyond Universal Saliency: Personalized Saliency Prediction with Multi-task CNN. IJCAI 2017: 3887-3893

8.Weixin Luo, Wen Liu, Shenghua Gao: A Revisit of Sparse Coding Based Anomaly Detection in Stacked RNN Framework, ICCV 2017

9.Kui Jia, Dacheng Tao, Shenghua Gao: Improving training of deep neural networks via Singular Value Bounding. CVPR 2017

10.Weixin Luo,Wen, Liu, Shenghua Gao: REMEMBERING HISTORY WITH CONVOLUTIONAL LSTM FOR ANOMALY DETETION. ICME 2017