Jun-Jie Huang
MPhil (PolyU), PhD, DIC (Imperial College London)
Email:
I am now an Associate Professor at the College of Computer Science and Technology, National University of Defense Technology (NUDT), Changsha, Hunan, China.
I earned my Ph.D. (2019) at the Department of Electrical and Electronic Engineering, Imperial College London, under the supervision of Professor Pier Luigi Dragotti. I received the B.Eng. (Hons) degree (2013) with First Class Honours in Electronic Engineering from The Hong Kong Polytechnic University and the M.Phil. degree (2015) in Electronic and Information Engineering from the same university under the supervision of Professor Wan-Chi Siu.
During 2019 - 2021, I was a postdoctoral research associate at Communications and Signal Processing Group, Electrical and Electronic Engineering Department, Imperial College London, advised by Professor Pier Luigi Dragotti.
My research interests include multi-modal processing, model-based deep learning, and computer vision.
I have published over 60 papers in prestigious journals and conferences, including IEEE TPAMI, TIP, TNNLS, TSP, TCSVT, AAAI, NeurIPS, ACM MM. Full list of publications available on Google Scholar.
I am currently looking for highly motivated Master students. All interested candidates are welcome to apply. Kindly send your CV to me via email.
What's New
2025-07 One paper on Video Summarization has been accepted by ACM MM 2025 (CCF-A), congratulations to Yamiao!
2025-04 One paper on Multi-View Clustering has been accepted by IJCAI 2025 (CCF-A), congratulations to all co-authors!
2025-03 One paper on Large Multi-modal Model for Network Traffic Analysis has been accepted by ACM CCS 2025 (CCF-A)!
2025-03 Four papers have been accepted by IEEE ICME 2025 (CCF-B)!
2025-03 One paper has been accepted by IEEE DSN 2025 (CCF-B)!
2025-03 The journal version of our ICASSP'24 paper on single image reflection removal has been accepted by IEEE T-PAMI (CCF-A), congratulations to all co-authors!
2025-02 One paper has been accepted by IEEE T-FIS (CCF-A), congratulations Luming!
Selected Awards
2022 Top-notch Talent Support Program of NUDT (NUDT拔尖人才计划)
2021 Hundred Talent Program of Hunan Province, China (湖南“百人计划”海外高层次引进人才)
2019 Chinese Government Award for Outstanding Self-financed Students Abroad (国家优秀自费留学生奖学金)
Current Students
Zihan Chen, Multi-Task Image Restoration, (PhD Student, 2024 - ) Co-supervise with Prof. Wentao Zhao
Yankun Wang, Generative Flow, (PhD Student, 2024 - ) Co-supervise with Prof. Yongjun Wang
Qian Yao, AIGC Detection, (PhD Student, 2024 - ) Co-supervise with Prof. Yongjun Wang
Chenbo Huang, Object Re-identification, (PhD Student, 2024 - ) Co-supervise with Prof. Yuanxi Peng
Yi Pan, Video Adversarial Attack, (Master Student, 2022 - ) Co-supervise with Prof. Wentao Zhao
Maoyi Xiong, Diffusion Model for Image Fusion, (Master Student, 2023 - ) Co-supervise with Prof. Wentao Zhao
Boya Miao, Test-Time Training, (PhD Student, 2024 - ) Co-supervise with Prof. Xuejun Yang, Prof. Wenjing Yang
Former Students
Xiao Liu, Graph Adversarial Attack, (PhD Student, 2019 - 2024) Co-supervise with Prof. Wentao Zhao
Ziyue Wang, Physical World Adversarial Patch Attack for Remote Sensing Images, (Master Student, 2021 - 2023) Co-supervise with Prof. Wentao Zhao
Zihan Chen, Image Hiding based on Invertible Neural Network, (Master Student, 2021 - 2023) Co-supervise with Prof. Wentao Zhao
Yankun Wang, Website Fingerprinting Defense for Tor Network, (Master Student, 2021 - 2023) Co-supervise with Prof. Yongjun Wang
Academic Talks
Invertible Neural Networks and Their Applications, IEEE SPS Webinar, July 2024
Journal Paper
2. Luming Yang, Yongjun Wang, Lin Liu, Jun-Jie Huang, Jiangyong Shi, and Shaojing Fu,
"unFlowS: An Unsupervised Construction Scheme of Flow Spectrum for Network Traffic Detection,"
IEEE Transactions on Information Forensics and Security, 2025.
3. Yu Gan, Yunning You, Jun-Jie Huang, Sen Xiang, Chang Tang, Wei Hu, and Shan An,
"Multi-view Clustering via Multi-stage Fusion,"
IEEE Transactions on Multimedia, 2025.
4. Jun-Jie Huang#, Ziyue Wang#, Tianrui Liu*, Wenhan Luo, Zihan Chen, Wentao Zhao*, and Meng Wang,
"DeMPAA: Deployable Multi-Mini-Patch Adversarial Attack for Remote Sensing Image Classification,"
IEEE Transactions on Geoscience and Remote Sensing, 2024. (# co-first author, * corresponding author)
5. Chuan Tang, Kun Sun, Chang Tang, Xiao Zheng, Xinwang Liu, Jun-Jie Huang, Wei Zhang,
"Multi-view subspace clustering via adaptive graph learning and late fusion alignment,"
Neural Networks, 2024.
6. Vincent C. H. Leung, Jun-Jie Huang, Yonina C. Eldar, Pier Luigi Dragotti,
"Learning-based Reconstruction of FRI Signals,"
IEEE Transactions on Signal Processing, 2023.
7. Su Yan, Jun-Jie Huang, Herman Verinaz-Jadan, Nathan Daly, Catherine Higgit, and Pier Luigi Dragotti,
"A Fast Automatic Method for Deconvoluting Macro X-ray Fluorescence Data Collected from Easel Paintings,"
IEEE Transactions on Computational Imaging, 2023.
8. Barak Sober, Spike Bucklow, Nathan Daly, Ingrid Daubechies,
Pier Luigi Dragotti, Catherine Higgit, Jun-Jie Huang,
Aleksandra Piˇzurica, Wei Pu, Suzanne Reynold, Miguel Rodrigue, Carola-Bibiane Sch ̈onlieb,
and Su Yan, "Revealing and Reconstructing Hidden or Lost Features in Art Investigation,"
IEEE BITS the Information Theory Magazine, 2022.
10. Wei Pu#, Jun-Jie Huang#*, Barak Sober, Nathan Daly, Catherine Higgitt, Ingrid Daubechies, Pier Luigi Dragotti, and Miguel Rodigues, "Mixed X-Ray Image Separation for Artworks with Concealed Designs,"
IEEE Trans. on Image Processing, vol.31, pp. 4458 - 4473, June 2022. (# co-first author, * corresponding author)
13. Su Yan, Jun-Jie Huang*, Nathan Daly, Catherine Higgitt and Pier Luigi Dragotti, "
When de Prony Met Leonardo: An Automatic Algorithm for Chemical Element Extraction from Macro X-ray Fluorescence Data,"
IEEE Trans. on Computational Imaging, vol. 7, pp. 908-924, 2021. (*Corresponding author)
15. Tianrui Liu, Wenhan Luo, Lin Ma, Jun-Jie Huang*, Tania Stathaki and Tianhong Dai, "
Coupled Network for Robust Pedestrian Detection with Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling,"
IEEE Trans. on Image Processing, vol. 30, pp. 754-766, 2021. (*Corresponding author)
17. Jun-Jie Huang and Pier Luigi Dragotti,
"Photo Realistic Image Completion via Dense Correspondence,"
IEEE Trans. on Image Processing, vol 27, no. 11, pp. 5234-5247, November 2018.
18. Jun-Jie Huang and Wan-Chi Siu,
"Learning Hierarchical Decision Trees for Single Image Super-Resolution,"
IEEE Trans. on Circuits and Systems for Video Technology, vol. 27, no. 5, pp. 937-950, 2017.
(State-of-the-art image super-resolution results!)
19. Jun-Jie Huang, Wan-Chi Siu and Tian-Rui Liu,
"Fast Image Interpolation via Random Forests," IEEE Trans. on Image Processing, vol. 24, no. 10, pp. 3232-3245, 2015.
(State-of-the-art image interpolation results!)
Conference Paper
1.Yi Pan, Jun-Jie Huang, Zihan Chen, Wentao Zhao, and Ziyue Wang,
"SVASTIN: Sparse Video Adversarial Attack via Spatio-Temporal Invertible Neural Networks,"
2024 IEEE International Conference on Multimedia and Expo (ICME), 2024.
5. Yankun Wang, Yongjun Wang, Jun-Jie Huang, and Yongxin Chen,
"TBP: Tree structure Burst-sequence Padding Defense Against Website Fingerprinting,"
2023 IEEE International Performance, Computing, and Communications Conference (IPCCC), 2023.
6. Yuting Yang, Lin Liu, Shaojing Fu, Jun-Jie Huang, and Yuchuan Luo,
"SecGAN: Honest-Majority Maliciously 3PC Framework for Privacy-Preserving Image Synthesis,"
2023 IEEE International Performance, Computing, and Communications Conference (IPCCC), 2023.
7. Ziyue Wang, Jun-Jie Huang, Tianrui Liu, et. al.,
"Multi-patch adversarial attack for remote sensing image classification,"
Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data, 2023.
8.Su Ya, Herman Verinaz-Jadan, Jun-Jie Huang, Nathan Daly, Catherine Higgitt, and Pier Luigi Dragotti,
"Super-Resolution For Macro X-Ray Fluorescence Data Collected From Old Master Paintings,"
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.
10. Weixuan Liang, Xinwang Liu, Yong Liu, Sihang zhou, Jun-Jie Huang, Siwei Wang, Jiyuan Liu, Yi Zhang, and En Zhu,
"Stability and Generalization of Kernel Clustering: from Single Kernel to Multiple Kernel,"
Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS) 2022.
11. Renke Wang, Jun-Jie Huang, and Pier Luigi Dragotti,
"FRISPEE: FRI-Based Single Image Super-Resolution with Deep Recursive Residual Network,"
European Signal Processing Conference (EUSIPCO) 2022.
13. Wei Pu, Jun-Jie Huang, Barak Sober, Nathan Daly, Catherine Higgitt, Pier Luigi Dragotti, Ingrid Daubechies, Miguel Rodrigues,
"A Learning Based Approach to Separate Mixed X-Ray Images Associated with Artwork with Concealed Designs,"
European Signal Processing Conference (EUSIPCO) 2021.
14. Vincent C. H. Leung, Jun-Jie Huang, Yonina C. Eldar, Pier Luigi Dragotti,
"Reconstruction of FRI Signals using Autoencoder with Fixed Decoder,"
European Signal Processing Conference (EUSIPCO) 2021.
16. Vincent Chi Hang Leung, Jun-Jie Huang, and Pier Luigi Dragotti,
"Reconstruction of FRI Signals using Deep Neural Network Approaches,"
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’2020). (Oral)
17. Su Yan, Jun-Jie Huang, Nathan Daly, Catherine Higgitt, and Pier Luigi Dragotti,
"Revealing Hidden Drawings in Leonardo's 'The Virgin of the Rocks' from MACRO X-RAY Fluorescence Scanning Data through Element Line Localisation,"
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’2020). (Oral)
21. Jun-Jie Huang, and Pier Luigi Dragotti, "A Deep Dictionary Model for Image Super-Resolution,"
Proceedings, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’2018).
(oral presentation @ Special Session on Learning Signal Representation using Deep Learning).
23. Jun-Jie Huang, Tianrui Liu, Pier Luigi Dragotti, and Tania Stathaki,
"SRHRF+: Self-Example Enhanced Single Image Super-Resolution Using Hierarchical Random Forests,"
Proceedings, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshop on New Trends in Image Restoration and Enhancement, July 2017.
Teaching
Convex Optimization (Spring 2023, 2024)
Machine Learning (Fall 2023)