Adaptive Variance-Threshold-Based Skip Modes for Learned Video Compression Using a Motion Complexity Criterion
Brand F, Seiler J, Sauer J, Alshina E, Kaup A (2024)
Publication Type: Conference contribution
Publication year: 2024
Publisher: Institute of Electrical and Electronics Engineers Inc.
Conference Proceedings Title: 2024 Picture Coding Symposium, PCS 2024 - Proceedings
Event location: Taichung, TWN
ISBN: 9798350358483
DOI: 10.1109/PCS60826.2024.10566348
Abstract
Skip modes are a powerful tool to reduce the rate in video compression. The main idea is that the residual areas where the prediction performs well are not transmitted since the prediction quality is good enough that the prediction signal itself can be used as the reconstruction signal. This is commonly used, e.g., in the compression standard VVC, where a skip flag can be transmitted for inter blocks under certain conditions. The skipped residual block is then not transmitted and the content is instead inferred to be zero at the decoder. Current learning-based methods use different kinds of skip modes. One possibility here arises from the fact that the coders estimate and transmit the variance for each transmitted symbol. It has been proposed to use this estimated variance to derive a skip mode. When the variance falls below a threshold, the symbol is not transmitted. In this paper we propose an extension to this method. By classifying each position in the latent space according to the local motion complexity, we can transmit adaptive thresholds for each class. That way, we can employ motion information to refine the granularity of the skip mode. When we implement this method in FVC, we are able to save up 2.11% rate on a GOP 20 sequence. We also discuss the behavior of increasingly adaptive skip modes in scenarios with larger GOP size, where error-propagation becomes a larger issue.
Authors with CRIS profile
Fabian Brand
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Jürgen Seiler
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Andre Kaup
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Involved external institutions
Germany (DE)How to cite
APA:
Brand, F., Seiler, J., Sauer, J., Alshina, E., & Kaup, A. (2024). Adaptive Variance-Threshold-Based Skip Modes for Learned Video Compression Using a Motion Complexity Criterion. In 2024 Picture Coding Symposium, PCS 2024 - Proceedings. Taichung, TWN: Institute of Electrical and Electronics Engineers Inc..
MLA:
Brand, Fabian, et al. "Adaptive Variance-Threshold-Based Skip Modes for Learned Video Compression Using a Motion Complexity Criterion." Proceedings of the 2024 Picture Coding Symposium, PCS 2024, Taichung, TWN Institute of Electrical and Electronics Engineers Inc., 2024.
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