2026 2nd International Conference on Image Processing and Deep Learning has successfully concluded!

From March 06 to 08, 2025, the 2026 2nd International Conference on Image Processing and Deep Learning hosted by Chongqing University , were successfully held in Chongqing, China.

The event was marked by a highly engaging atmosphere, with scholars and experts actively discussing the latest research and applications in the fields of Image Processing and Deep Learning. It was a fruitful exchange of ideas and insights!

The conference featured outstanding keynote presentations by renowned experts, including Professor Jianping Gou, IEEE Senior Member,Southwest University,China; Professor Yulin Wang, IEEE Senior Member, Wuhan University, China; Professor Lu Leng, IEEE Member,Nanchang Hangkong University,China and associate Professor Zhi Wang from Southwest University,China.

Professor Lei Zhang summarizes unified theory as a pivotal approach to addressing dual challenges in visual perception. He provides an overview of the trade-offs between robustness and generalization in computer vision, followed by a detailed discussion of the theoretical foundations, classical algorithms, and application scenarios of his proposed unified framework, and concludes with insights into its future development..

Professor Mang Ye summarizes multimodal large language models as pivotal components in modern artificial intelligence. He provides an overview of the challenges in model adaptation, followed by a detailed discussion of the theory, classical algorithms, and application scenarios of continual learning and safe tuning, and concludes with insights into their future development.

Professor Zhong Zhang summarizes deep learning as a transformative force in meteorological observation. He provides an overview of traditional cloud observation methods, followed by a detailed discussion of the theory, classical algorithms, and application scenarios of deep neural networks in ground-based cloud analysis, and concludes with insights into their future development.

Professor Jianping Gou summarizes knowledge distillation as a simple and effective technique for compressing large models in deep learning. He provides an overview of large models and model compression, followed by a detailed discussion of the theory, classical algorithms, and application scenarios of model distillation, and concludes with insights into its future development.

The successful hosting of this conference provides a high-end academic exchange platform for professionals in the fields of Image Processing and Deep Learning. In the future, we look forward to more international academic conferences like IPDL 2026, which will continue to promote academic exchanges and cooperation worldwide, and jointly promote technological innovation and development in these fields. I believe that with the joint efforts of all sectors, the future of Image Processing and Deep Learning will be full of infinite possibilities, making greater contributions to the progress of human society.

Thank you to all the speakers, attendees, and staff who participated in this conference. Although IPDL 2026 has come to an end, our exploration and research in the fields of Image Processing and Deep Learning and Computational Intelligence will never stop. Looking forward to our next gathering!