Versatile Video Coding

Versatile Video Coding (VVC) aims to achieve highly efficient video compression, surpassing previous standards in rate-distortion performance. Current research focuses on improving VVC's efficiency and applicability through techniques like neural network-based in-loop filtering, optimized motion models, and content-specific post-processing filters, often leveraging convolutional neural networks (CNNs) and autoencoders. These advancements are significant because they address VVC's high computational complexity and enable its adaptation for diverse applications, including machine vision tasks where traditional codecs may be suboptimal. The resulting improvements in compression efficiency and task-specific optimization have broad implications for various fields relying on video processing and transmission.