TRACK 1: Computer Vision and Recognition
			Computer vision is a rapidly advancing field of artificial 
			intelligence that enables computer systems to interpret and 
			understand visual information from the environment. Recent 
			breakthroughs in deep learning, image processing, and hardware have 
			driven significant advancements in computer vision and recognition 
			technology. Today, computer vision and recognition are widely used 
			in various fields, including automotive driving, manufacturing, 
			healthcare, robotics, media, fashion, and security. This conference 
			track aims to bring together researchers, practitioners, and 
			industry experts to discuss the latest trends, techniques, and 
			challenges in computer vision and recognition. Attendees will have 
			the opportunity to explore cutting-edge research, share best 
			practices, and collaborate on new ideas and solutions for advancing 
			the field.
Track Chairs:
     Prof. Hongtao Lu, Shanghai Jiao Tong University, China
     Prof. Yuchun Fang, Shanghai University, China
			
			Track Program Chairs:
     Assoc. Prof. Fei Jiang, East China Normal University, China
			
			Track Technical Committee:
     Asst. Prof. Tamam Alsarhan, Applied Science Private 
			University, Jordan
     Asst. Prof. Yue Ding, Shanghai Jiao Tong University
     Assoc. Prof. Haiyan Li, Kashi University, India
     Assoc. Prof. Hongbin Yu, Jiangnan University, China
Topics of interest include, but are not limited 
			to:
    ◆ Image and Video Classification
    
			◆ Object Detection and Tracking
    ◆ Semantic 
			Segmentation
    ◆ Content-based Image Retrieval
    
			◆ Facial Recognition
    ◆ 3D Reconstructions
    ◆ Action Recognition 
			Submission Guidelines
Please submit your manuscript via 
			
			Electronic 
			Submission System (account is needed). 
			(Please choose the track number when you make the submission.)
Important Dates
    ◆ Submission of Full Papers: 
			Jan. 25, 2026
    ◆ Notification of Review Result 
			of Papers from Track: Feb. 15, 2026
    ◆ 
			Registration Deadline: Mar. 25, 2025
