Emerging Trends in Advanced Video and Sequence Technology

Dear Colleagues,

With the expansion of short-video applications, video surveillance, intelligent video analysis, as well as general sensor-based sequence processing, such as lidar or mobile sensors, and combined video/sensor applications, such as autonomous driving, video and general sequences have become more and more popular. With the rich information brought by the video and general sequences, it also poses new challenges in coding, transmission, processing, and analysis. Advanced video and sequence technologies are highly desired.

On the other hand, many new sequence processing techniques have been developed, especially in the era of deep learning, such as the transformer and IndRNN (Independently Recurrent Neural Network). Many conventional video/sequence methods have been renovated, or even completely replaced with deep learning. With the strong power of new tools, it starts a new age for the advanced video and sequence technologies.

This Special Issue focuses on the emerging trends in advanced video and sequence technologies, including new video/sequence applications and datasets, new video/sequence processing methods, and new general tools for video/sequence tasks. Prospective authors are invited to submit high-quality original contributions and reviews to this Special Issue. Specific topics of interest include, but are not limited to:

• Video coding, including deep learning enhanced methods, fully deep learning-based methods;
• Video processing, including super-resolution, denoising;
• 3D video processing, including video-based depth estimation, vision based autonomous driving;
• Video/sequence-based recognition, including action recognition, skeleton-based action recognition, video-based object detection/segmentation, smartphone-based recognition;
• New video/sequence representation format, including light field, virtual reality;
• Various sequence applications and processing methods;
• New tools for video/sequence processing, including enhanced and specialized transformer, IndRNN, and others.

Prof. Dr. Shuai Li 
Dr. Yanbo Gao
Dr. Chuankun Li
Dr. Jin Wang
Prof. Dr. Yimin Zhou
Guest Editors

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