Dear Colleagues,

Multimedia and visual computing are important research areas in the fields of machine learning and computer vision. Over the past decade, various types of visual content have shown rapid expansion, including texts, images, videos, point clouds, and so on. It is essential to represent and understand such a large amount of visual content for multimedia and visual computing tasks. Meanwhile, the rise of artificial intelligence (AI) technology is able to provide effective support for deriving valuable information from various types of visual content. However, due to the complex characteristics of real-world visual content, there are still some difficulties in handling multimedia and visual computing tasks with existing AI-driven algorithms. Therefore, it is significant to explore advanced multimedia and visual computing methods for practical applications, thus promoting the development of an intelligent society.

The purpose of this Special Issue is to collect and publish new ideas, the latest findings, and state-of-the-art achievements on the topic of challenges and applications in multimedia and visual computing.

Topics of interest include, but are not limited to:

1. Advanced visual feature learning and representation methods;
2. Advanced classification, recognition, and retrieval methods;
3. Advanced 2D/3D object detection and tracking methods;
4. Advanced multi-modal learning and analysis methods;
5. Advanced stereo, multi-view, and 3D content processing methods;
6. Advanced image/video synthesis, editing, and visualization methods;
7. Advanced image/video restoration and enhancement methods in low-level vision;
8. Advanced quality assessment methods for multimedia;
9. Advanced image/video compression and intelligent analysis methods;
10. Zero-shot/few-shot methods for visual computing and multimedia;
11. Unsupervised/self-supervised/weakly supervised methods for visual computing and multimedia.

Prof. Dr. Jianjun Lei
Dr. Bo Peng
Prof. Dr. Shuai Li
Dr. Bin Yi
Guest Editors

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• image/video processing
• image/video compression
• quality assessment
• restoration and enhancement
• representation learning
• recognition and retrieval
• 3D processing
• multi-modal learning
• multimedia analysis