Predictive Coding For Animation-Based Video Compression
This work addresses video compression for conferencing, offering incremental improvements over existing animation-based methods by enhancing reconstruction quality at higher bandwidths.
The paper tackles the problem of compressing video for conferencing applications by proposing a predictive coding scheme that uses image animation as a predictor and codes residuals, achieving over 70% bitrate gain compared to HEVC and over 30% compared to VVC on talking-head videos.
We address the problem of efficiently compressing video for conferencing-type applications. We build on recent approaches based on image animation, which can achieve good reconstruction quality at very low bitrate by representing face motions with a compact set of sparse keypoints. However, these methods encode video in a frame-by-frame fashion, i.e. each frame is reconstructed from a reference frame, which limits the reconstruction quality when the bandwidth is larger. Instead, we propose a predictive coding scheme which uses image animation as a predictor, and codes the residual with respect to the actual target frame. The residuals can be in turn coded in a predictive manner, thus removing efficiently temporal dependencies. Our experiments indicate a significant bitrate gain, in excess of 70% compared to the HEVC video standard and over 30% compared to VVC, on a datasetof talking-head videos