8 papers
LANCE: Locally Adaptive Neural Context Estimation for Overfitted Image Compression
Martin Benjak, Jörn Ostermann
This paper introduces Locally Adaptive Neural Context Estimation (LANCE), a novel extension for overfitted image compression (OIC) frameworks like Cool-Chic. While traditional OIC…
On Optimizing Image Codecs for VMAF NEG: Analysis, Issues, and a Robust Loss Proposal
Florian Fingscheidt, Alexander Karabutov, Panqi Jia +2
The VMAF (video multi-method assessment fusion) metric for image and video coding recently gained more and more popularity as it is supposed to have a high correlation with human p…
A Cross-Framework Study of Temporal Information Buffering Strategies for Learned Video Compression
Kuan-Wei Ho, Yi-Hsin Chen, Martin Benjak +2
Recent advances in learned video codecs have demonstrated remarkable compression efficiency. Two fundamental design aspects are critical: the choice of inter-frame coding framework…
HyTIP: Hybrid Temporal Information Propagation for Masked Conditional Residual Video Coding
Yi-Hsin Chen, Yi-Chen Yao, Kuan-Wei Ho +5
Most frame-based learned video codecs can be interpreted as recurrent neural networks (RNNs) propagating reference information along the temporal dimension. This work revisits the…
Comp-X: On Defining an Interactive Learned Image Compression Paradigm With Expert-driven LLM Agent
Yixin Gao, Xin Li, Xiaohan Pan +7
We present Comp-X, the first intelligently interactive image compression paradigm empowered by the impressive reasoning capability of large language model (LLM) agent. Notably, com…
Conditional Residual Coding with Explicit-Implicit Temporal Buffering for Learned Video Compression
Yi-Hsin Chen, Kuan-Wei Ho, Martin Benjak +2
This work proposes a hybrid, explicit-implicit temporal buffering scheme for conditional residual video coding. Recent conditional coding methods propagate implicit temporal inform…
On the Rate-Distortion-Complexity Trade-offs of Neural Video Coding
Yi-Hsin Chen, Kuan-Wei Ho, Martin Benjak +2
This paper aims to delve into the rate-distortion-complexity trade-offs of modern neural video coding. Recent years have witnessed much research effort being focused on exploring t…
MaskCRT: Masked Conditional Residual Transformer for Learned Video Compression
Yi-Hsin Chen, Hong-Sheng Xie, Cheng-Wei Chen +4
Conditional coding has lately emerged as the mainstream approach to learned video compression. However, a recent study shows that it may perform worse than residual coding when the…