Special Session 3  会议特别专题 3

Underwater Vision Processing

Description: Approximately 71% of the Earth's surface is covered by water, and the absorption, scattering, and attenuation of light in aquatic environments pose significant challenges to underwater vision tasks. Current challenges include unclear imaging of underwater vision, difficulties of target detection and tracking, and inaccuracies of light-field reconstruction and depth estimation. However, with remarkable advancements in artificial intelligence, modern vision technologies—machine learning and deep learning—offer innovative solutions to these above problems. Research on underwater image processing is crucial for developing key technologies in maritime power strategies. This special issue, titled "Underwater Vision Processing", summarizes recently key technologies and their applications, covering underwater image restoration and enhancement, underwater image quality assessment, underwater object detection and tracking, underwater image depth estimation, underwater light-field reconstruction, underwater 3D scene reconstruction, underwater imaging and compression, and related methods on enhancing other harsh environments (such as haze, dust, and low-light, etc.).

Session organizers
Assoc. Prof. Peixian Zhuang, University of Science and Technology Beijing, China
Assoc. Prof. Weiling Chen, Fuzhou University, China
Assoc. Prof. Yang Ou, Chengdu University, China
Senior Engineer Yi Zhu, Xiamen University, China
Dr. Zhenqi Fu, Tsinghua University, China

The topics of interest include, but are not limited to:
▪ Underwater Image Restoration and Enhancement
▪ Underwater Image Quality Evaluation
▪ Underwater Object Detection and Tracking
▪ Underwater Image Depth Estimation
▪ Underwater Light-Field Image Reconstruction
▪ Underwater 3D Scene Reconstruction
▪ Underwater Imaging and Compression
▪ Image enhancement in harsh environment (haze, dust, and low-light, etc.)

Submission method
Submit your Full Paper (no less than 5 pages with two colums) or your paper abstract-without publication (200-400 words) via Online Submission System, then choose Special Session 3 (Underwater Vision Processing)
Template Download

Introduction of Session organizers

Assoc. Prof. Peixian Zhuang, University of Science and Technology Beijing, China

Peixian Zhuang received the Ph.D. degree from Xiamen University in 2016. From 2020 to 2022, He was a Postdoctoral Researcher in Tsinghua University. He is currently an Associate Professor at University of Science and Technology Beijing. He is an IEEE Senior Member, and his research interests involve underwater image processing, and artificial intelligence. He has published more than 60 papers (10 ESI Highly Cited and 6 ESI Hot Papers) in top-tier international journals and conferences, including IEEE TIP, TCSVT, TCYB, TGRS, TMM, with over 3700 Google citations. He also has authored 1 English book and 10 Chinese invention patents. In recent years, he has presided over a number of underwater vision processing projects, including National Natural Science Foundation of China, China Postdoctoral Science Foundation, and has participated in National Key Research and Development Program of China. He was entitled "Young Scientist for Marine Power Nation", ScholarGPS "World's Top 0.05% Scholars", "World's Top 2% Scientists", "IFAC EAAI Best Paper Award", and "Outstanding Doctoral Dissertation in Fujian Province". Besides, he has served as Regional Chair of ICIGP and Session Chair of IEEE ICSIP, Youth Editorial Board Members of multiple journals, Guest Editor of the Journal of Image & Graphics, Guest Editor of the Journal of Electronics & Information Technology, etc.



Assoc. Prof. Weiling Chen, Fuzhou University, China

Weiling Chen received the Ph.D. degree from Xiamen University. Currently, she is an Associate Professor and Master's Supervisor in the College of Physics and Information Engineering at Fuzhou University, and is also recognized as a High-Level Talent in Fujian Province. Her main research interests include intelligent oceanography, computer vision, underwater acoustic communication, etc. She has published more than 50 peer-reviewed papers in journals and conferences such as IEEE TIP, IEEE TMM, TGRS, IEEE JoE, IEEE OCEANS. She has presided over projects including the National Natural Science Foundation of China and the Natural Science Foundation of Fujian Province, and has participated in projects such as the National Key R&D Program of China and the Fujian Provincial Key Technological Innovation and Industrialization Project in Manufacturing. Currently, she serves as an Associate Editor for IEEE Signal Processing Letters, an Editorial Board Member for Scientific Reports, a Youth Editorial Board Member for the Journal of Marine Information, and a Youth Editorial Board Member for the Journal of Hainan University. She has received the Science and Technology Progress Award from the Fujian Association of Artificial Intelligence as the first completer. She has also served as a Forum Chair for conferences such as IEEE OCEANS, CSIG CCIG, CSIG Young Scientist Forum, and ChinaMM.



Assoc. Prof. Yang Ou, Chengdu University, China

Yang Ou received the Ph.D. degree from Southwest Jiaotong University in 2022. He was a Research Scholar with Concordia University, Montreal, Canada, from 2021 to 2022. From 2022 to 2025, he was a Lecture with School of Mechanical Engineering at Chengdu University. From 2026 to now, he is an Associate Professor with School of Mechanical Engineering at Chengdu University. His main research interests include underwater image enhancement, image restoration, and pattern recognition. He has published more than 30 peer-reviewed papers in prestigious international journals, and he has also served as Workshop Chair for ICRAIC-2025, and ICCVIT-2025.



Senior Engineer Yi Zhu, Xiamen University, China

Yi Zhu received the Master of Engineering degree in Information and Communication Engineering from Xiamen University in 2014. From August 2014 to July 2015, he served as a Project Manager of the Network Department at China Mobile Group Fujian Co., Ltd. Fuzhou Branch. From August 2015 to July 2018, he worked as an Assistant Engineer at the School of Information Science and Technology, Xiamen University. From August 2018 to July 2025, he served as an Engineer at the School of Informatics, Xiamen University. From August 2025 to present, he has been a Senior Engineer at the School of Informatics, Xiamen University. Since joining Xiamen University, he has also been a core technical support member of the Key Laboratory of Underwater Acoustic Communication and Marine Information Technology (Xiamen University), Ministry of Education of the People's Republic of China. His main research interests include underwater signal acquisition and edge-side intelligent processing, underwater acoustic communication and marine information technology, intelligent analysis and enhancement of multimedia signals, research and development of Internet of Things and intelligent systems, practical teaching of electronic information and innovative talent training, etc. He has published more than 20 peer-reviewed academic papers in prestigious domestic and international journals and conferences. He has won 1 first prize in national-level teaching competitions, and has guided students to win 2 first prizes and 5 second prizes in national-level teaching competitions.



Dr. Zhenqi Fu, Tsinghua University, China

Zhenqi Fu received the Ph.D. degree in Signal and Information Processing from Xiamen University, Xiamen, China, in 2023. From 2021 to 2022, he was a Visiting Ph.D. Student at the School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore. He is currently a postdoctoral researcher in the Department of Automation, Tsinghua University, Beijing, China. He has published over 20 peer-reviewed SCI/EI-indexed papers and has served as a reviewer for top-tier journals and conferences, including IEEE TPAMI, IEEE TIP, IJCV, ICLR, ICML, NeurIPS, CVPR, ICCV, ECCV, etc. His current research interests include Low-level Vision, Biomedical Imaging, and Deep Learning.