Video Codecs

Video codecs aim to efficiently compress and decompress video data, balancing compression ratio with visual quality. Current research focuses on developing neural video codecs, employing architectures like hierarchical predictive learning, implicit neural representations (INRs), and transformer networks, often incorporating techniques like optical flow analysis and adaptive quality control to improve rate-distortion performance. These advancements are driven by the need for efficient video transmission and storage in various applications, particularly in scenarios with bandwidth limitations or resource-constrained devices, and are leading to improved objective and subjective quality metrics for evaluating these codecs. Furthermore, research is exploring the adaptation of video codecs for machine vision tasks, optimizing compression for downstream analysis rather than solely human perception.