1 citations · 4 across the 8 of their papers we have counts for
8 papers
Transformer-based Learned Image Compression for Joint Decoding and Denoising
Yi-Hsin Chen, Kuan-Wei Ho, Shiau-Rung Tsai +4
This work introduces a Transformer-based image compression system. It has the flexibility to switch between the standard image reconstruction and the denoising reconstruction from…
OMRA: Online Motion Resolution Adaptation to Remedy Domain Shift in Learned Hierarchical B-frame Coding
Zong-Lin Gao, Sang NguyenQuang, Wen-Hsiao Peng +1
Learned hierarchical B-frame coding aims to leverage bi-directional reference frames for better coding efficiency. However, the domain shift between training and test scenarios due…
Transformer-based Image Compression with Variable Image Quality Objectives
Chia-Hao Kao, Yi-Hsin Chen, Cheng Chien +2
This paper presents a Transformer-based image compression system that allows for a variable image quality objective according to the user's preference. Optimizing a learned codec f…
CANF-VC++: Enhancing Conditional Augmented Normalizing Flows for Video Compression with Advanced Techniques
Peng-Yu Chen, Wen-Hsiao Peng
Video has become the predominant medium for information dissemination, driving the need for efficient video codecs. Recent advancements in learned video compression have shown prom…
Learning Continuous Exposure Value Representations for Single-Image HDR Reconstruction
Su-Kai Chen, Hung-Lin Yen, Yu-Lun Liu +4
Deep learning is commonly used to reconstruct HDR images from LDR images. LDR stack-based methods are used for single-image HDR reconstruction, generating an HDR image from a deep…
Hierarchical B-frame Video Coding Using Two-Layer CANF without Motion Coding
David Alexandre, Hsueh-Ming Hang, Wen-Hsiao Peng
Typical video compression systems consist of two main modules: motion coding and residual coding. This general architecture is adopted by classical coding schemes (such as internat…