7 papers · 1 filter
Exploiting Semantic and Pixel Representations for Ultra-Low Bitrate Image Compression
Hao Wei, Yanhui Zhou, Chenyang Ge +2
Most existing extreme compression methods fail to achieve an optimal rate-distortion-perception trade-off, as they typically prioritize perceptual fidelity and visual realism over…
SAMIC: A Lightweight Semantic-Aware Mamba for Efficient Perceptual Image Compression
Jiaqian Zhang, Hao Wei, Chenyang Ge +1
Perceptual image compression focuses on preserving high visual quality under low-bitrate constraints. Most existing approaches to perceptual compression leverage the strong generat…
Faithful Extreme Image Rescaling with Learnable Reversible Transformation and Semantic Priors
Hao Wei, Yanhui Zhou, Chenyang Ge +2
Most recent extreme rescaling methods struggle to preserve semantically consistent structures and produce realistic details, due to the severely ill-posed nature of low- to high-re…
Geometric Transformation-Embedded Mamba for Learned Video Compression
Hao Wei, Yanhui Zhou, Chenyang Ge
Although learned video compression methods have exhibited outstanding performance, most of them typically follow a hybrid coding paradigm that requires explicit motion estimation a…
One-Step Diffusion for Perceptual Image Compression
Yiwen Jia, Hao Wei, Yanhui Zhou +1
Diffusion-based image compression methods have achieved notable progress, delivering high perceptual quality at low bitrates. However, their practical deployment is hindered by sig…
RGB Guided ToF Imaging System: A Survey of Deep Learning-based Methods
Xin Qiao, Matteo Poggi, Pengchao Deng +3
Integrating an RGB camera into a ToF imaging system has become a significant technique for perceiving the real world. The RGB guided ToF imaging system is crucial to several applic…