Unlocking the future of image and video coding with AI-based Image and Video Coding: Methods, Standards, and Applications, we can explore the revolutionary impact of deep learning technologies on image and video compression. This book is a must-read for researchers, practitioners, and students eager to stay ahead of the curve in an ever-evolving field where deep learning and artificial intelligence are setting new benchmarks in coding efficiency.

With an unparalleled focus on the intersection of deep learning and multimedia coding, this book offers cutting-edge insights into the latest techniques and standards driving progress in the industry. From the core principles of coding technologies to advanced topics like 3D and multimodal coding, human and machine vision-oriented compression, and compression artifacts removal, it covers all the related essentials. Special attention is given to the practical aspects of implementations, open-source projects, and standardization efforts from leading organizations like IEEE, JPEG, MPEG and MPAI.

Whether you are a scholar, a professional in the multimedia industry, or a student with a foundation in computer science and electrical engineering, this book equips you with the fundamental knowledge and tools to master the latest advancements in AI-based image and video coding. You can gain a deeper understanding of how deep learning reshapes the future of image and video coding, and explore new possibilities of optimizing compression performances for both humans and machines.

Autorentext

Wei Gao is an Assistant Professor at the School of Electronic and Computer Engineering, Peking University, Shenzhen, China. He earned his Ph.D. in Computer Science from the City University of Hong Kong in February 2017. Dr. Gao's research focuses on multimedia coding, multimedia processing, and multimodal learning, areas directly relevant to the topics explored in this book.

With over 160 high-quality technical papers published, Dr. Gao has contributed significantly to multimedia coding standardization, submitting more than 50 technical proposals. He is the author or co-author of two influential books, and is an elected member of the IEEE Visual Signal Processing and Communications Technical Committee (VSPC-TC), and APSIPA Image Video and Multimedia Technical Committee (IVM-TC). He serves on the editorial board of Elsevier Signal Processing*,* and has organized workshops at prominent conferences such as IEEE ICME and ACM MM.

In addition to his academic achievements, Dr. Gao leads several open-source projects, including OpenAICoding*,* OpenPointCloud, and OpenDatasets, providing valuable resources for the research community. As a Senior Member of IEEE, he is also a frequent speaker at international conferences, where he shares his expertise on deep learning and multimedia technologies.