History

The 2026 International Conference on Computer Vision, Graphics, and Artificial Intelligence (CVGAI 2026) was convened with great success from June 26 to 28, 2026, at Zhoukou Normal University, located in Zhoukou City, Henan Province, China. The conference programme was thoughtfully structured into two principal segments: the Main Forum and parallel breakout sessions, ensuring a comprehensive and dynamic academic agenda. To facilitate broad and in-depth scholarly exchange, CVGAI 2026 featured a rich variety of presentation formats, including invited keynote lectures, contributed oral presentations, and interactive poster sessions. The event drew a distinguished assembly of academics, researchers, and industry professionals from leading universities, research institutions, and corporate sectors worldwide. Serving as a premier interdisciplinary platform for global scientific dialogue, the conference fostered vibrant discussions on cutting-edge technological advances and transformative industrial developments across the interrelated domains of computer vision, graphics, and artificial intelligence.

微信图片_20260629112553_74_16.jpg

The conference was hosted by Zhoukou Normal University and organized by the School of Artificial Intelligence at Zhoukou Normal University. At the opening ceremony, Dr. Xu Kun, Associate Dean of the School of Artificial Intelligence, delivered a welcome address, while Dr. Wang Wei, also Associate Dean of the School, presided over the opening session.


微信图片_20260629112805_75_16.jpg微信图片_20260629112924_93_16.jpg


During the keynote session, distinguished speakers presented groundbreaking academic achievements, including Prof. Gao Wei from the Institute of Automation, Chinese Academy of Sciences; Prof. Yang Lei from Zhengzhou University; Prof. Chai Xiuli from Henan University; Prof. Zhang Fenghui from West Anhui University; and Associate Prof. Chen Lei from Shandong University.


Prof. Wei Gao, Institute of Automation, Chinese Academy of Sciences, China

Title: Monocular Vision Navigation for Mobile Robots in Unknown Environments


Prof. Lei Yang, Zhengzhou University, China

Title: Research and Progress on Recognition Methods for Mixed Wafer Map Defects


Prof. Xiuli Chai, Henan University, China

Title: Visual Content Privacy Protection Preserving Availability


Prof. Fenghui Zhang, West Anhui University, China

Title: Edge Intelligence for Future Connected Systems: From Game-Theoretic Optimization to Deep Reinforcement Learning


Assoc. Prof. Lei Chen, Shandong University, China

Title: Multi-Modal Spatio-Temporal Modeling Methods for Video Anomaly Detection


微信图片_20260629115750_77_64.jpg


In addition to the keynote presentations, a series of specialized oral sessions were delivered by scholars from multiple institutions, including Zhoukou Normal University, West Anhui University, the Chinese People's Liberation Army Medical School, the Shanghai Aircraft Design and Research Institute, and Korea University. The presentations covered a wide range of cutting-edge research topics, such as agricultural robot perception, multimodal emotion recognition, aviation fluid prediction, crop disease identification, intelligent navigation for craniomaxillofacial surgery, and optimization models for anomaly detection.


微信图片_20260629115412_76_64.jpg


This conference has significantly advanced the innovation and real-world application of interdisciplinary technologies spanning computer vision, graphics, and artificial intelligence. By bringing together leading global intellect and cutting-edge insights, CVGAI 2026 has injected strong technological momentum into the high-quality development of the intelligent digital economy.

To enhance your experience, with your consent for all our websites and applications, we (and our partners) store and/or access information on your device (cookies or corresponding information) when you connect. Our website may use these cookies to:
Determine the audience of advertisements on our website without collecting data
Display personalized ads based on your browsing and profile
Personalize our editorial content according to your navigation
Allow you to share content on social networks or platforms on our website
Accept All
Reject All