B Frame

B-frame video compression focuses on efficiently encoding intermediate frames in a video sequence by leveraging information from both preceding and succeeding frames, aiming to achieve higher compression ratios than solely using forward prediction (P-frames). Current research emphasizes developing deep learning models, often employing architectures like conditional augmented normalizing flows (CANF) or incorporating techniques such as bi-directional motion estimation and interpolation, to improve the accuracy and efficiency of B-frame coding. These advancements are significant because they promise to reduce storage and bandwidth requirements for video, impacting various applications from video streaming to virtual and augmented reality.