Fushuo Huo (霍赋硕) Pervasive Intelligence Lab (PEILAB) Department of Computing (COMP) The Hong Kong Polytechnic University Location: PQ Wing, PolyU, Kowloon, Hong Kong SAR. Research Interest | Education | Publications | Awards Email: fushuo.huo@connect.polyu.hk;      Phone: +86 18751795276 [Google Scholar] [Github] [Wechat]

Research Interest

• Trustworthy AI; Elastic AI
• Multimodal Learning; Vision-language Model

Education & Experience

• 2022.09-2025.09 (expected)
  Ph.D. , supervised by Prof. Song Guo and Wenchao Xu, Hong Kong Polytechnic University.     
• 2024.10-2025.09 (expected)
  Visiting Ph.D. , supervised by Prof. Dacheng Tao, Nanyang Technological University.     
• 2019.09-2022.06
  M.S. , supervised by Prof. Xuegui Zhu and Prof. Lei Zhang, Chongqing University.        
• 2015.09-2019.06
  B.S. , (Minor in Finance) China University of Mining and Technology.         
• 2024.04-2024.11
  Research Intern , supervised by Dr. Zhong Zhang and Dr. Peilin Zhao, Tencent AI Lab.     

Publications

[1] Y. Fan, W. Xu, H. Wang, F. Huo, J. Chen, and S. Guo, “Overcome Modal Bias in Multi-modal Federated Learning via Balanced Modality Selection,” European Conference on Computer Vision (ECCV), 2024. [Paper]

[2] F. Huo, W. Xu, J. Guo, H. Wang, and S. Guo, “C2KD: Bridging the Modality Gap for Cross-Modal Knowledge Distillation,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, Highlight. [Paper]

[3] F. Huo, W. Xu, S. Guo, J. Guo, H. Wang, and Z. Liu, “PROCC: Progressive cross-primitive consistency for open-world compositional zero-shot learning,” Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024. [Paper]

[4] F. Huo, W. Xu, J. Guo, H. Wang, Y. Fan, and S. Guo, “Non-Exemplar Online Class-incremental Continual Learning via Dual-prototype Self-augment and Refinement,” Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024. [Paper]

[5] B. Li, F. Huo* (Corresponding Author), “REQA: Coarse-to-fine Assessment of Image Quality to Alleviate the Range Effect,” Journal of Visual Communication and Image Representation, 2024. [Paper]

[6] F. Huo, Z. Liu, J. Guo, W. Xu, and S. Guo, “UTDNet: A unified triplet decoder network for multimodal salient object detection,” Neural Networks, 2023. [Paper]

[7] J. Guo, S. Guo, Q. Zhou, Z. Liu, X. Lu, and F. Huo, “Graph knows unknowns: Reformulate zero-shot learning as sample-level graph recognition,” Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023. [Paper]

[8] Z. Liu, S. Guo, X. Lu, J. Guo, J. Zhang, Y. Zeng, and F. Huo, “(ML)$^2$P-Encoder: On Exploration of Channel-Class Correlation for Multi-Label Zero-Shot Learning,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023. [Paper]

[9] Z. Liu, S. Guo, J. Guo, Y. Xu, and F. Huo, “Towards Unbiased Multi-Label Zero-Shot Learning with Pyramid and Semantic Attention,” IEEE Transactions on Multimedia, 2022. [Paper]

[10] F. Huo, X Zhu, and B Li, “Three-stream interaction decoder network for RGB-thermal salient object detection,” Knowledge-Based Systems, 2022. [Paper]

[11] X. Zhu, Y. Shu, Q. Zhang, and F. Huo, “Spatiotemporal regularization correlation filter with response feedback,” Journal of Electronic Imaging, 2022. [Paper]

[12] F. Huo, X. Zhu, Q. Zhang, Z. Liu, and W. Yu, “Real-time One-stream Semantic-guided Refinement Network for RGB-Thermal Salient Object Detection,” IEEE Transactions on Instrumentation and Measurement, 2022. [Paper]

[13] F. Huo, X. Zhu, L. Zhang, Q. Liu, and Y. Shu, “Efficient Context-Guided Stacked Refinement Network for RGB-T Salient Object Detection,” IEEE Transactions on Circuits and Systems for Video Technology, 2022. [Paper]

[14] F. Huo, B. Li, X. Zhu, “Efficient Wavelet Boost Learning-Based Multi-stage Progressive Refinement Network for Underwater Image Enhancement,” International Conference on Computer Vision Workshop (ICCVW) in Advances in Image Manipulation, [Paper]

[15] F. Huo, X. Zhu, H. Zeng, Q. Liu, and J. Qiu, “Fast Fusion-Based Dehazing With Histogram Modification and Improved Atmospheric Illumination Prior,” IEEE Sensors Journal, 2021. [Paper]

[16] X. Zhu, Y. Shu, C. Peng, F. Huo, and W. Zhu, “Transient Electromagnetic Voltage Imaging of Dense UXO-Like Targets Based on Improved Mathematical Morphology,” IEEE Access, 2020. [Paper]

Awards

• 2022, Excellent Master Thesis, School of Electrical Engineering. | 电气工程学院优秀硕士学位论文
• 2021, National Scholarship of China, Ministry of Education. | 国家奖学金
• 2019, The First-class Academic Scholarship, Chongqing University. | 重庆大学一等奖学金
• 2017, Second Prize of Jiangsu Mathematics Competition. | 江苏省数学竞赛二等奖
• 2016, National Encouragement Scholarship, Ministry of Education. | 国家励志奖学金