Dr. Gengshen Wu
Assistant Professor Ph.D./Master’s Supervisor
Programme Coordinator (Master Program)
Email:gswu@cityu.edu.mo
Tel:(853)85902289
Office address: Room N502, Choi Kai Yau Building, City University of Macau (Taipa)
Academic Qualifications
Doctor of Philosophy in Computer Science, Lancaster University, UK
Research Interests
Multimedia retrieval, Machine learning applications, Computer vision
Research and publishing
• Liu, Y., Zhou, L., Wu, G., Xu, S., Han, J., 2023. TCGNet: type-correlation guidance for salient object detection. IEEE Transactions on Intelligent Transportation Systems.
• Wu, H., Wu, G.∗, Hu, J., Xu, S., Zhang, S., Liu, Y., 2023. CityUPlaces: a new dataset for efficient vision-based recognition. Journal of Real- Time Image Processing.
• Kong, Y., Zhang, K., Zhang, L., Wu, G., 2023. Deep Facial Attribute Analysis. Frontiers in Neuroscience, 17, p.1280831.
• Wu, G., Lin, Z., Ding, Ni, Q. and Han, J. “On Aggregation of Unsupervised Deep Binary Descriptor with Weak Bits.” IEEE Transactions on Image Processing, 2020.
• Wu, G., Han, J., Guo, Y., Liu, L., Ding, G., Ni, Q. and Shao, L., 2019. Unsupervised Deep Video Hashing via Balanced Code for Large-Scale Video Retrieval. IEEE Transactions on Image Processing, 28(4), pp.1993- 2007.
• Wu, G., Han, J., Lin, Z., Ding, G., Zhang, B. and Ni, Q., 2018. Joint Image-Text Hashing for Fast Large-Scale Cross-Media Retrieval Using Self- Supervised Deep Learning. IEEE Transactions on Industrial Electronics.
• Wu, G., Lin, Z., Han, J., Liu, L., Ding, G., Zhang, B. and Shen, J., 2018. Unsupervised Deep Hashing via Binary Latent Factor Models for Largescale Cross- modal Retrieval. IJCAI (pp. 2854-2860).
• Wu, G., Liu, L., Guo, Y., Ding, G., Han, J., Shen, J. and Shao, L., 2017, August. Unsupervised deep video hashing with balanced rotation. IJCAI.
• Qi, Y., Gu, J., Zhang, Y., Wu, G., and Wang, F. “Supervised Deep Semantics-Preserving Hashing for RealTime Pulmonary Nodule Image Retrieval.” in Journal of Real-Time Image Processing, 2020.
• Zhang, S., Wu. G., Gu. J. and Han, J. “Pruning Filter with Attention Mechanism for Deep Networks Compression on Remote Sensing Image.” in Electronics, 2020.
Scientific research project experience
1. Macau Science and Technology Development Fund (FDCT) Project: Cross-modal fast image and text retrieval based on deep hashing technology (Project No.: 0004/2023/ITP1), Hosted, 2023/11-2025/08
2. National Natural Science Foundation of China (NSFC) general project: Multi-sensor image/video fusion based on sparse representation and visual attention mechanism (Project No.: 61773301), participation, 2018/01-2021/12
3. Cooperation project between National Natural Science Foundation of China (NSFC) and Royal Society (RS): RGB-D cross-view object recognition applied to large-scale data (NSFC: 6151101259, RS: IE150997), participation, 2016/04-2018/ 03

