Neural video compression with diverse contexts
For any video codecs, the coding efficiency highly relies on whether the current signal to be
encoded can find the relevant contexts from the previous reconstructed signals. Traditional …
encoded can find the relevant contexts from the previous reconstructed signals. Traditional …
Hinerv: Video compression with hierarchical encoding-based neural representation
Learning-based video compression is currently a popular research topic, offering the
potential to compete with conventional standard video codecs. In this context, Implicit Neural …
potential to compete with conventional standard video codecs. In this context, Implicit Neural …
Neural video compression with feature modulation
The emerging conditional coding-based neural video codec (NVC) shows superiority over
commonly-used residual coding-based codec and the latest NVC already claims to …
commonly-used residual coding-based codec and the latest NVC already claims to …
Learned rate control for frame-level adaptive neural video compression via dynamic neural network
C Zhang, W Gao - European conference on computer vision, 2024 - Springer
Abstract Neural Video Compression (NVC) has achieved remarkable performance in recent
years. However, precise rate control remains a challenge due to the inherent limitations of …
years. However, precise rate control remains a challenge due to the inherent limitations of …
LSVC: A learning-based stereo video compression framework
In this work, we propose the first end-to-end optimized framework for compressing
automotive stereo videos (ie, stereo videos from autonomous driving applications) from both …
automotive stereo videos (ie, stereo videos from autonomous driving applications) from both …
Non-semantics suppressed mask learning for unsupervised video semantic compression
Most video compression methods aim to improve the decoded video visual quality, instead
of particularly guaranteeing the semantic-completeness, which deteriorates downstream …
of particularly guaranteeing the semantic-completeness, which deteriorates downstream …
Motion information propagation for neural video compression
In most existing neural video codecs, the information flow therein is uni-directional, where
only motion coding provides motion vectors for frame coding. In this paper, we argue that …
only motion coding provides motion vectors for frame coding. In this paper, we argue that …
[PDF][PDF] Overview of Intelligent Signal Processing Systems
ABSTRACT Niklaus Emil Wirth introduced the innovative concept of Programming=
Algorithm+ Data Structure [109]. Inspired by this, we advance the concept to the next level by …
Algorithm+ Data Structure [109]. Inspired by this, we advance the concept to the next level by …
Complexity-guided slimmable decoder for efficient deep video compression
In this work, we propose the complexity-guided slimmable decoder (cgSlimDecoder) in
combination with skip-adaptive entropy coding (SaEC) for efficient deep video compression …
combination with skip-adaptive entropy coding (SaEC) for efficient deep video compression …
Mmvc: Learned multi-mode video compression with block-based prediction mode selection and density-adaptive entropy coding
Learning-based video compression has been extensively studied over the past years, but it
still has limitations in adapting to various motion patterns and entropy models. In this paper …
still has limitations in adapting to various motion patterns and entropy models. In this paper …