TY - GEN
T1 - Predictive Coding for Animation-Based Video Compression
AU - Konuko, Goluck
AU - Lathuilière, Stéphane
AU - Valenzise, Giuseppe
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - 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 dataset of talking-head videos.
AB - 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 dataset of talking-head videos.
KW - Video compression
KW - generative models
KW - image animation
KW - predictive coding
KW - video conferencing
UR - https://www.scopus.com/pages/publications/85178072485
U2 - 10.1109/ICIP49359.2023.10222205
DO - 10.1109/ICIP49359.2023.10222205
M3 - Conference contribution
AN - SCOPUS:85178072485
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 2810
EP - 2814
BT - 2023 IEEE International Conference on Image Processing, ICIP 2023 - Proceedings
PB - IEEE Computer Society
T2 - 30th IEEE International Conference on Image Processing, ICIP 2023
Y2 - 8 October 2023 through 11 October 2023
ER -