Deep Learning Based Video Compression

Deep learning is revolutionizing video compression, aiming to achieve higher compression ratios while maintaining or improving visual quality compared to traditional methods. Current research focuses on improving model architectures, such as incorporating transformers for better long-range dependency modeling and hybrid approaches combining deep learning with conventional codecs for enhanced efficiency and reduced computational cost. These advancements are significant for reducing bandwidth requirements in various applications, from video streaming and conferencing to internet of things (IoT) devices, while also impacting the robustness of video compression systems against adversarial attacks.